Not-critical chunks offer histograms, gamma values, default background colors, and, finally, text.
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Two sparse histograms of bamboo poles line the sides, like the posts of an ill-defended tropical fort.
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Article of the Day Before reading the article: How comfortable are you with reading graphs, including charts, maps and histograms?
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The histograms have 1-year intervals for age on the x-axis, and their percentage frequency on the y-axis.
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The histograms below show the results of 23,215 model simulations estimating support, with the mean estimate marked with a red bar.
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To simplify the task of spotting anomalies, CORVIDS turns the possible data sets into histograms and arranges them into a three-dimensional chart.
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A huge part of the Object Explorer is visualizing data, which can be done in four main ways: numeric charts, histograms, timelines, and pie charts.
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That's right: R can import data from formats like Excel and turn it into histograms, scatterplots, and more, so you won't have to explain all the mathematical details when you show your findings.
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Equi-depth histograms will experience this issue to some degree, but because the equi-depth construction is simpler, there is a lower cost to maintain it. The difficulty in updating VOptimal histograms is an outgrowth of the difficulty involved in constructing these histograms.
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Histograms are most commonly used as visual representations of data. However, Database systems use histograms to summarize data internally and provide size estimates for queries. These histograms are not presented to users or displayed visually, so a wider range of options are available for their construction. Simple or exotic histograms are defined by four parameters, Sort Value, Source Value, Partition Class and Partition Rule.
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Histogram specification transforms the red, green and blue histograms to match the shapes of three specific histograms, rather than simply equalizing them. It refers to a class of image transforms which aims to obtain images of which the histograms have a desired shape. As specified, firstly it is necessary to convert the image so that it has a particular histogram. Assume an image x.
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Local dosimetry is possible and isodose curved and dose-volume histograms can be calculated.
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Still, algorithms like classification, filter kernels and general convolutions, histograms, and Discrete Fourier Transform are expressible.
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Implementation of this rule is a complex problem and construction of these histograms is also a complex process.
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Histogram of travel time (to work), US 2000 census. Histograms depict the frequencies of observations occurring in certain ranges of values In statistics the frequency (or absolute frequency) of an event i is the number n_i of times the observation occurred/recorded in an experiment or study. These frequencies are often graphically represented in histograms.
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The left histogram appears to indicate that the upper half has a higher density than the lower half, whereas the reverse is the case for the right-hand histogram, confirming that histograms are highly sensitive to the placement of the anchor point. Comparison of 2D histograms. Left. Histogram with anchor point at (−1.5, -1.5). Right.
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The idea behind V-optimal histograms is to minimize the variance inside each bucket. In considering this, a thought occurs that the variance of any set with one member is 0. This is the idea behind "End-Biased" V-optimal Histograms. The value with the highest frequency is always placed in its own bucket.
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Pyramid match kernel is a fast algorithm (linear complexity instead of classic one in quadratic complexity) kernel function (satisfying Mercer's condition) which maps the BoW features, or set of features in high dimension, to multi- dimensional multi-resolution histograms. An advantage of these multi- resolution histograms is their ability to capture co-occurring features. The pyramid match kernel builds multi-resolution histograms by binning data points into discrete regions of increasing size. Thus, points that do not match at high resolutions have the chance to match at low resolutions.
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Search by matching 3D conformation of molecules or by specifying spatial constraints is another feature that is particularly of use in drug design. Searches of this kind can be computationally very expensive. Many approximate methods have been proposed, for instance BCUTS, special function representations, moments of inertia, ray-tracing histograms, maximum distance histograms, shape multipoles to name a few.
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The target histograms are also examined, as changes in mode reflectances and in population are likely the result of changes in calibration.
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Histogram equalization is a method in image processing of contrast adjustment using the image's histogram. Histograms of an image before and after equalization.
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The Yoix distribution also includes a Yoix package, called Byzgraf, for rendering basic data plots such as line charts, histograms and statistical box plots.
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Cosmic crystallographers use cosmic separation histograms to infer characteristics of the universe. Large spikes are expected to appear if the universe is not simply connected.
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This problem can often be mitigated by using camera tonal settings that allow the JPEG histograms and highlight-clipping indictors to best reflect the underlying raw data.
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Improvements in picture brightness and contrast can thus be obtained. In the field of computer vision, image histograms can be useful tools for thresholding. Because the information contained in the graph is a representation of pixel distribution as a function of tonal variation, image histograms can be analyzed for peaks and/or valleys. This threshold value can then be used for edge detection, image segmentation, and co-occurrence matrices.
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The magnitudes are further weighted by a Gaussian function with \sigma equal to one half the width of the descriptor window. The descriptor then becomes a vector of all the values of these histograms. Since there are 4 × 4 = 16 histograms each with 8 bins the vector has 128 elements. This vector is then normalized to unit length in order to enhance invariance to affine changes in illumination.
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Histogram with anchor point at (−1.625, −1.625). Both histograms have a bin width of 0.5, so differences in appearances of the two histograms are due to the placement of the anchor point. One possible solution to this anchor point placement problem is to remove the histogram binning grid completely. In the left figure below, a kernel (represented by the grey lines) is centred at each of the 50 data points above.
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The Cox model extends the log-rank test by allowing the inclusion of additional covariates. This example use the melanoma data set where the predictor variables include a continuous covariate, the thickness of the tumor (variable name = "thick"). Histograms of melanoma tumor thickness In the histograms, the thickness values don't look normally distributed. Regression models, including the Cox model, generally give more reliable results with normally-distributed variables.
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Her innovative method uses a model that sharpens the peaks of the measured attenuation histograms of the images to minimize noise while preventing too much smoothing of the data.
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Put another way, histogram-based algorithms have no concept of a generic 'cup', and a model of a red and white cup is no use when given an otherwise identical blue and white cup. Another problem is that color histograms have high sensitivity to noisy interference such as lighting intensity changes and quantization errors. High dimensionality (bins) color histograms are also another issue. Some color histogram feature spaces often occupy more than one hundred dimensions.
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In neurophysiology, peristimulus time histogram and poststimulus time histogram, both abbreviated PSTH or PST histogram, are histograms of the times at which neurons fire. It is also sometimes called pre event time histogram or PETH. These histograms are used to visualize the rate and timing of neuronal spike discharges in relation to an external stimulus or event. The peristimulus time histogram is sometimes called perievent time histogram, and post-stimulus and peri-stimulus are often hyphenated.
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The program generates read-only story visualization and analysis diagrams, including a variety of histograms and a social graph. Descriptive information can be provided for individual acts, sequences, characters, and so forth.
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The BMRB provides a collection of NMR statistical data, including chemical shift distributions for individual atoms in amino acids, ribonucleotides and deoxyribonucleotides. The data are presented as interactive histograms and density plots.
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The main drawback of histograms for classification is that the representation is dependent of the color of the object being studied, ignoring its shape and texture. Color histograms can potentially be identical for two images with different object content which happens to share color information. Conversely, without spatial or shape information, similar objects of different color may be indistinguishable based solely on color histogram comparisons. There is no way to distinguish a red and white cup from a red and white plate.
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Given two images, the reference and the target images, we compute their histograms. Following, we calculate the cumulative distribution functions of the two images' histograms – F_1()\, for the reference image and F_2()\, for the target image. Then for each gray level G_1\in[0,255], we find the gray level G_2\, for which F_1(G_1)=F_2(G_2)\,, and this is the result of histogram matching function: M(G_1)=G_2\,. Finally, we apply the function M() on each pixel of the reference image.
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V-optimal histograms do a better job of estimating the bucket contents. A histogram is an estimation of the base data, and any histogram will have errors. The partition rule used in VOptimal histograms attempts to have the smallest variance possible among the buckets, which provides for a smaller error. Research done by Poosala and Ioannidis 1 has demonstrated that the most accurate estimation of data is done with a VOptimal histogram using value as a sort parameter and frequency as a source parameter.
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At this point, however, the buckets must carry additional information indicating what data values are present in the bucket. These histograms have been shown to be less accurate, due to the additional layer of estimation required.
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They combined HOG descriptors on individual video frames with their newly introduced internal motion histograms (IMH) on pairs of subsequent video frames. These internal motion histograms use the gradient magnitudes from optical flow fields obtained from two consecutive frames. These gradient magnitudes are then used in the same manner as those produced from static image data within the HOG descriptor approach. When testing on two large datasets taken from several movies, the combined HOG-IMH method yielded a miss rate of approximately 0.1 at a 10^{-4} false positive rate.
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The two may be combined in Two Phase Optimization, or 2PO. These algorithms are put forth in "Randomized Algorithms..." (cited below) as a method to optimize queries, but the general idea may be applied to construction of V-optimal Histograms.
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Andrea Miglio and collaborators noticed that both types of histograms were spitting images of one another, as can be seen in the histograms picture. Moreover, adding the knowledge of the distances of these thousands of stars to their galactic coordinates, a 3D map of our galaxy was drawn. This is illustrated in the figure where different colors relate to different CoRoT runs and to Kepler observations (green points). # Age-metallicity relation in our galaxy: The age of a red giant is closely related to its former main sequence lifetime, which is in turn determined by its mass and metallicity.
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Many earthquake engineers work on the problem of better defining the world data on building properties.Porter, K. A., K. S. Jaiswal, D. J. Wald, M. Greene, and C. Comartin (2008). WHE-PAGER Project: a new initiative in estimating global building inventory and its seismic vulnerability, 14th World Conf. Earthq. Eng., Beijing, China, Paper S23-016 After one knows the distribution of buildings into classes (histograms on the left in both frames of Figure 4), one needs to estimate how the population is distributed into these building types (histograms on the right in both frames of Figure 4).
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The essential thought behind the histogram of oriented gradients descriptor is that local object appearance and shape within an image can be described by the distribution of intensity gradients or edge directions. The image is divided into small connected regions called cells, and for the pixels within each cell, a histogram of gradient directions is compiled. The descriptor is the concatenation of these histograms. For improved accuracy, the local histograms can be contrast-normalized by calculating a measure of the intensity across a larger region of the image, called a block, and then using this value to normalize all cells within the block.
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Experimental observation of optical rogue waves. Single-shot time traces for three different pump power levels (increasing from top to bottom) and corresponding histograms. Each time trace contains ~15,000 events. Rogue events reach intensities of at least 30–40 times the average value.
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Resources, like Facilities and Storages represent limited capacity resources. Computational entities, like Ampervariables (variables), Functions and random generators are used to represent the state of Transactions or elements of their environment. Statistical entities, like Queues or Tables (histograms) collect statistical information of interest.
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Neighboring pixels are combined after thresholding into a ternary pattern. Computing a histogram of these ternary values will result in a large range, so the ternary pattern is split into two binary patterns. Histograms are concatenated to generate a descriptor double the size of LBP.
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The online data can be presented by PAW as histograms and N-tuples as well as by ROOT. A dedicated HTTP server gives fast Web access for experiment control and to access the slow control system including a graphical representation of variable trends (history display).
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Image SXM supports image stacks, a series of images that share a single window. It can calculate area and pixel value statistics of user-defined selections and intensity thresholded objects. It can measure distances and angles. It can create density histograms and line profile plots.
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We take an illustrative synthetic bivariate data set of 50 points to illustrate the construction of histograms. This requires the choice of an anchor point (the lower left corner of the histogram grid). For the histogram on the left, we choose (−1.5, −1.5): for the one on the right, we shift the anchor point by 0.125 in both directions to (−1.625, −1.625). Both histograms have a binwidth of 0.5, so any differences are due to the change in the anchor point only. The colour-coding indicates the number of data points which fall into a bin: 0=white, 1=pale yellow, 2=bright yellow, 3=orange, 4=red.
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Histograms are sometimes confused with bar charts. A histogram is used for continuous data, where the bins represent ranges of data, while a bar chart is a plot of categorical variables. Some authors recommend that bar charts have gaps between the rectangles to clarify the distinction.
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Journal of Computational Information Systems, 7(5), 1516-1523. # Otsu, N. A threshold selection method from gray-level histograms. IEEE Trans Systems, Man and Cybernetics,9(1):62-66, 1979. # Gebäck1, T. & Koumoutsakos, P. "Edge detection in microscopy images using curvelets" BMC Bioinformatics, 10: 75, 2009.
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The final step is tracking. This is done by associating moving objects in present and past frame. For object tracking, segment matching is adopted. Features such as mean, standard deviation, quantized color histograms, volume size and number of 3-D points of a segment are computed.
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Pearson brought his correlation formula to his own Biometrics Laboratory. Pearson had volunteer and salaried computers who were both men and women. Alice Lee was one of his salaried computers who worked with histograms and the chi-squared statistics. Pearson also worked with Beatrice and Frances Cave-Brown-Cave.
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The color histogram may also be represented and displayed as a smooth function defined over the color space that approximates the pixel counts. Like other kinds of histograms, the color histogram is a statistic that can be viewed as an approximation of an underlying continuous distribution of colors values.
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Applied to the construction of V-optimal histograms, the initial random state would be a set of values representing the bucket boundary placements. The iterative improvement steps would involve moving each boundary until it was at its local minimum, then moving to the next boundary and adjusting it accordingly.
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Relative species abundance distributions are usually graphed as frequency histograms ("Preston plots"; Figure 2) or rank-abundance diagrams ("Whittaker Plots"; Figure 3).Whittaker, R. H. 1965. "Dominance and diversity in land plant communities", Science 147: 250–260 Frequency histogram (Preston plot): ::x-axis: logarithm of abundance bins (historically log2 as a rough approximation to the natural logarithm) ::y-axis: number of species at given abundance Rank-abundance diagram (Whittaker plot): ::x-axis: species list, ranked in order of descending abundance (i.e. from common to rare) ::y-axis: logarithm of % relative abundance When plotted in these ways, relative species abundances from wildly different data sets show similar patterns: frequency histograms tend to be right-skewed (e.g.
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It can measure distances and angles. It can create density histograms and line profile plots. It supports standard image processing functions such as logical and arithmetical operations between images, contrast manipulation, convolution, Fourier analysis, sharpening, smoothing, edge detection, and median filtering. It does geometric transformations such as scaling, rotation, and flips.
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The apoptotic DNA fragmentation is being used as a marker of apoptosis and for identification of apoptotic cells either via the DNA laddering assay, the TUNEL assay, or the by detection of cells with fractional DNA content ("sub G1 cells") on DNA content frequency histograms e.g. as in the Nicoletti assay.
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Dee, H. M. and Caplier, A. "Crowd behaviour analysis using histograms of motion direction", IEEE International Conference on Image Processing (ICIP), 2010, Hong Kong. Santos, P. E., Dee, H. M. and Fenelon, V. "Knowledge-based adaptative thresholding from shadows" Accepted at the European Conference on Artificial Intelligence (ECAI), 2010, Lisbon, Portugal.
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Examples of distribution strategies include: constant values, event list, constant interval spacing, normal distribution, exponential distribution, and so forth. Priority determines the processing strategy if two inputs reach a process at the same time. Higher priority inputs are usually processed before lower priority inputs. Sample Histograms Showing Results of a Simulation Run.
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They are graphic representations of processes, human and system resources, and their used capacity over time during a simulation run. These histograms are used to perform dynamic impact analysis of the behavior of the executable architecture. Figure 4-23 is an example showing the results of a simulation run of human resource capacity.
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It can also be used to create scatterplots, line graphs and histograms of data. This can include split plots, treatment combinations, as well as latin squares. DAP can perform linear regression and can utilize regressions to build linear models. In addition to linear regression, DAP can also perform logistic regression analysis as well.
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Cells can be manipulated by the acoustic forces directly, or by using microspheres as handles. With AFS devices it is possible to apply forces ranging from 0 to several hundreds of picoNewtons on hundreds of microspheres and obtain force-extension curves or histograms of rupture forces of many individual events in parallel.
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This is sometimes known as the extended Goldbach conjecture. The strong Goldbach conjecture is in fact very similar to the twin prime conjecture, and the two conjectures are believed to be of roughly comparable difficulty. The Goldbach partition functions shown here can be displayed as histograms, which informatively illustrate the above equations. See Goldbach's comet.
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Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density estimation with improved statistical properties. Apart from histograms, other types of density estimators include parametric, spline, wavelet and Fourier series.
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The pyramid match kernel performs an approximate similarity match, without explicit search or computation of distance. Instead, it intersects the histograms to approximate the optimal match. Accordingly, the computation time is only linear in the number of features. Compared with other kernel approaches, the pyramid match kernel is much faster, yet provides equivalent accuracy.
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BTF is also a spatially varying BRDF. To cope with a massive BTF data with high redundancy, many compression methods were proposed. Application of the BTF is in photorealistic material rendering of objects in virtual reality systems and for visual scene analysis, e.g., recognition of complex real-world materials using bidirectional feature histograms or 3D textons.
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Unlike other approaches, the lookup table method does not involve any filtering. It works by computing a distribution of the neighborhood for every pixel in the halftone image. The lookup table provides a continuous-tone value for a given pixel and its distribution. The corresponding lookup table is obtained before using histograms of halftone images and their corresponding originals.
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Charles Stangor (2011) "Research Methods For The Behavioral Sciences". Wadsworth, Cengage Learning. . Histograms give a rough sense of the density of the underlying distribution of the data, and often for density estimation: estimating the probability density function of the underlying variable. The total area of a histogram used for probability density is always normalized to 1.
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When this happens, we lose the contrast of the last 2 blocks, and thus, we cannot recover the image no matter how we adjust it. To conclude, when taking photos with a camera that displays histograms, always keep the brightest tone in the image below the largest scale 255 on the histogram in order to avoid losing details.
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Mondrian is a general-purpose statistical data-visualization system, for interactive data visualization. All plots in Mondrian are fully linked, and offer various interactions and queries. Any case selected in a plot in Mondrian is highlighted in all other plots. Currently implemented plots comprise Mosaic Plot, Scatterplots and SPLOM, Maps, Barcharts, Histograms, Missing Value Plot, Parallel Coordinates/Boxplots and Boxplots y by x.
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Another common feature detector is the SURF (speeded-up robust features). In SURF, the DOG is replaced with a Hessian matrix-based blob detector. Also, instead of evaluating the gradient histograms, SURF computes for the sums of gradient components and the sums of their absolute values. Its usage of integral images allows the features to be detected extremely quickly with high detection rate.
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Fit statistics are reported along with factor loadings and error variances. IRT methods include the Rasch, partial credit, and rating scale models. IRT equating methods include mean/mean, mean/sigma, Haebara, and Stocking-Lord procedures. jMetrik also includes IRT illustrator, a basic descriptive statistics and a graphics facility that produces bar charts, pie chart, histograms, kernel density estimates, and line plots.
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Dot plots may be distinguished from histograms in that dots are not spaced uniformly along the horizontal axis. Although the plot appears to be simple, its computation and the statistical theory underlying it are not simple. The algorithm for computing a dot plot is closely related to kernel density estimation. The size chosen for the dots affects the appearance of the plot.
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DBMS use statistic histograms to find data in a range against a table or index. Statistics updates should be scheduled frequently and sample as much of the underlying data as possible. Accurate and updated statistics allow query engines to make good decisions about execution plans, as well as efficiently locate data. Defragmentation of table and index data increases efficiency in accessing data.
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Once features have been detected, a local image patch around the feature can be extracted. This extraction may involve quite considerable amounts of image processing. The result is known as a feature descriptor or feature vector. Among the approaches that are used to feature description, one can mention N-jets and local histograms (see scale- invariant feature transform for one example of a local histogram descriptor).
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An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance. Image histograms are present on many modern digital cameras.
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A fit to the invariant mass spectrum for the decay, with each fit component shown individually. The contribution of the pentaquarks are shown by hatched histograms. The production of pentaquarks from electroweak decays of baryons has extremely small cross-section and yields very limited information about internal structure of pentaquarks. For this reason, there are several ongoing and proposed initiatives to study pentaquark production in other channels.
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The most frequently used nonlinear estimators of connectivity are mutual information, transfer entropy, generalised synchronisation, the continuity measure, synchronization likelihood, and phase synchronization. Mutual information and transfer entropy rely on the construction of histograms for probability estimates. The continuity measure, generalized synchronisations, and synchronisation likelihood are very similar methods based on phase space reconstruction. Among these measures, only transfer entropy allows for the determination of directionality.
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It encodes the underlying shape by accumulating local energy of the underlying signal along several filter orientations, several local histograms from different parts of the image/patch are generated and concatenated together into a 128-dimensional compact spatial histogram. It is designed to be scale invariant. The LESH features can be used in applications like shape-based image retrieval, medical image processing, object detection, and pose estimation.
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Shape histograms, feature vectors composed of global geo-metic properties such as circularity and eccentricity, and feature vectors created using frequency decomposition of spherical functions are common examples of using statistical methods to describe 3D information.Min, P., Kazhdan, M., Funkhouser, T., A comparison of text and shape matching for retrieval of Online 3D models. Research And Advanced Technology For Digital Libraries, 2004, Vol.3232, pp.
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The views are usually among the common tools of information visualization, such as histograms, scatterplots or parallel coordinates, but using volume rendered views is also possible if this is appropriate for the data. Typically, one view will display the independent variables of the dataset (e.g. time or spatial location), while the others display the dependent variables (e.g. temperature, pressure or population density) in relation to each other.
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For each of them, the frequency at maximum power νmax in the frequency spectrum as well as the large frequency separation between consecutive modes Δν could be measured, defining a sort of individual seismic passport. # Red giant population in our galaxy: Introducing these seismic signatures, together with an estimation of the effective temperature, in the scaling laws relating them to the global stellar properties, gravities (seismic gravities), masses and radii can be estimated and luminosities and distances immediately follow for those thousands of red giants. Histograms could then be drawn and a totally unexpected and spectacular result came out when comparing these CoRoT histograms with theoretical ones obtained from theoretical synthetic populations of red giants in our galaxy. Such theoretical populations were computed from stellar evolution models, with adopting various hypotheses to describe the successive generations of stars along the time evolution of our galaxy.
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Typically a Monte Carlo simulation using a Metropolis–Hastings update consists of a single stochastic process that evaluates the energy of the system and accepts/rejects updates based on the temperature T. At high temperatures updates that change the energy of the system are comparatively more probable. When the system is highly correlated, updates are rejected and the simulation is said to suffer from critical slowing down. If we were to run two simulations at temperatures separated by a ΔT, we would find that if ΔT is small enough, then the energy histograms obtained by collecting the values of the energies over a set of Monte Carlo steps N will create two distributions that will somewhat overlap. The overlap can be defined by the area of the histograms that falls over the same interval of energy values, normalized by the total number of samples.
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The idea behind compression techniques is to maintain only a synopsis of the data, but not all (raw) data points of the data stream. The algorithms range from selecting random data points called sampling to summarization using histograms, wavelets or sketching. One simple example of a compression is the continuous calculation of an average. Instead of memorizing each data point, the synopsis only holds the sum and the number of items.
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Wavelets are extracted individually for each well. A final "multi-well" wavelet is then extracted for each volume using the best individual well ties and used as input to the inversion. Histograms and variograms are generated for each stratigraphic layer and lithology, and preliminary simulations are run on small areas. The AVA geostatistical inversion is then run to generate the desired number of realizations, which match all the input data.
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Evaluating DNA histograms through flow cytometry provides an estimate of the fractions of cells within each of the phases in the cell cycle. Cell nuclei are stained with a DNA binding stain and the amount of staining is measured from the histogram. The fractions of cells within the different cell cycle phases (G0/G1, S and G2/M compartments) can then be calculated from the histogram by computerized cell cycle analysis.
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Illuminating the Path: The R&D; Agenda for Visual Analytics . National Visualization and Analytics Center. p.30 Data analysis is an indispensable part of all applied research and problem solving in industry. The most fundamental data analysis approaches are visualization (histograms, scatter plots, surface plots, tree maps, parallel coordinate plots, etc.), statistics (hypothesis test, regression, PCA, etc.), data mining (association mining, etc.), and machine learning methods (clustering, classification, decision trees, etc.).
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Histogramic intensity switching (HIS) is a vision-based obstacle avoidance algorithm developed in the lab. It makes use of histograms of images captured by a camera in real-time and does not make use of any distance measurements to achieve obstacle avoidance. An improved algorithm called the HIS-Dynamic mask allocation (HISDMA) has also been designed. The algorithms were tested on an in-house custom built robot called the VITAR.
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Engineering statistics combines engineering and statistics using scientific methods for analyzing data. Engineering statistics involves data concerning manufacturing processes such as: component dimensions, tolerances, type of material, and fabrication process control. There are many methods used in engineering analysis and they are often displayed as histograms to give a visual of the data as opposed to being just numerical. Examples of methods are:Hogg, Robert V. and Ledolter, J. (1992).
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Histograms for concordant Jack Hills zircons. This is a histogram of rapid initial survey of individual 207Pb/206Pb ages undertaken to identify the >4.2Ga population. There are 3 dominant peaks and 2 minor peaks.Holden P, Lanc P, Ireland TR, Harrison TM, Foster JJ, Bruce ZP (2009) Mass-spectrometric mining of Hadean zircons by automated SHRIMP multi-collector and single- collector U/Pb zircon age dating: The first 100 000 grains.
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Statistical distributions reveal trends based on how numbers are distributed. Common examples include histograms and box-and-whisker plots, which convey statistical features such as mean, median, and outliers. In addition to these common infographics, alternatives include stem-and-leaf plots, Q-Q plots, scatter plot matrices (SPLOM) and parallel coordinates. For assessing a collection of numbers and focusing on frequency distribution, stem-and-leaf plots can be helpful.
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GLOH (Gradient Location and Orientation Histogram) is a robust image descriptor that can be used in computer vision tasks. It is a SIFT-like descriptor that considers more spatial regions for the histograms. An intermediate vector is computed from 17 location and 16 orientation bins, for a total of 272-dimensions. Principal components analysis (PCA) is then used to reduce the vector size to 128 (same size as SIFT descriptor vector).
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The histograms provide the distribution before and after halftoning and make it possible to approximate the continuous-tone value for a specific distribution in the halftone image. For this approach, the halftoning strategy has to be known in advance for choosing a proper lookup table. Additionally, the table needs to be recomputed for every new halftoning pattern. Generating the descreened image is fast compared to iterative methods because it requires a lookup per pixel.
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In this case, a more accessible alternative can be plotting a series of stacked histograms or kernel density distributions. Violin plots are available as extensions to a number of software packages, including the R packages vioplot, wvioplot, caroline, UsingR, lattice and ggplot2, the Stata add-on command vioplot, and the Python libraries matplotlib, Plotly, ROOT and Seaborn, a graph type in Origin , IGOR Pro , Julia statistical plotting package StatsPlots.jl and DistributionChart in Mathematica.
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He projected the image onto the side and a vertical pixel image histogram was formed. The significant valleys of the resulting histograms served as a signature for the ends of text lines. When horizontal lines are detected, each lines are automatically cropped, and the histogram process repeats itself until all horizontal lines in the image have been identified. In order to determine the letter position, a similar process was carried out, but vertically this time.
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The above example is a simple one. There are only 7 choices of bucket boundaries. One could compute the cumulative variance for all 7 options easily and choose the absolute best placement. However, as the range of values gets larger and the number of buckets gets larger, the set of possible histograms grows exponentially and it becomes a dauntingly complex problem to find the set of boundaries that provide the absolute minimum variance.
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This method extracts local and global histograms to represent a certain object. To merge the results of 2-D image and 3-D space object detection, same 3-D region is considered and two independent classifiers from 2-D image and 3-D space are applied to the considered region. Scores calibration is done to get a single confidence score from both detectors. This single score is obtained in the form of probability.
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Some of their high profile users include: NASA, Nike, Amazon.com, Honda, Pixar, MIT Lincoln Laboratory, and The Olympic Games. The application enables users to organize tasks into project plans, assign resources to tasks, use effort driven scheduling, and view project details in Gantt charts, monthly calendars, and resource histograms, and more. FastTrack Schedule's capabilities are suited for project management beginnersPings & Packets from eWEEK Labs as well as experienced project managers working in small to mid- sized project teams.
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Area: Theory and Methods Best Paper Award: Jameson Reed, Mohammad Naeem and Pascal Matsakis. "A First Algorithm to Calculate Force Histograms in the Case of 3D Vector Objects" Best Student Paper: Johannes Herwig, Timm Linder and Josef Pauli. "Removing Motion Blur using Natural Image Statistics" Area: Applications Best Paper Award: Sebastian Kurtek, Chafik Samir and Lemlih Ouchchane. "Statistical Shape Model for Simulation of Realistic Endometrial Tissue" Best Student Paper: Florian Baumann, Jie Lao, Arne Ehlers and Bodo Rosenhahn.
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In data analysis, the self-similarity matrix is a graphical representation of similar sequences in a data series. Similarity can be explained by different measures, like spatial distance (distance matrix), correlation, or comparison of local histograms or spectral properties (e.g. IXEGRAM). This technique is also applied for the search of a given pattern in a long data series as in gene matching. A similarity plot can be the starting point for dot plots or recurrence plots.
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It involves data gathering and display in an attempt to understand the important aspects of the problem. 3\. Analysis: In this step the various tools of quality analysis are used, such as Control charts, Pareto charts, cause-and-effect diagrams, scatter diagrams, histograms, etc. 4\. Action: Based on the analysis, an action is taken. 5\. Study: The results are studied to see if they conform to what was expected and to learn from what was not expected.
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Univariate analysis involves describing the distribution of a single variable, including its central tendency (including the mean, median, and mode) and dispersion (including the range and quartiles of the data-set, and measures of spread such as the variance and standard deviation). The shape of the distribution may also be described via indices such as skewness and kurtosis. Characteristics of a variable's distribution may also be depicted in graphical or tabular format, including histograms and stem-and-leaf display.
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An example histogram of the heights of 31 Black Cherry trees. Histograms are a common tool used to represent data. Data is a set of values of qualitative or quantitative variables; restated, pieces of data are individual pieces of information. Data in computing (or data processing) is represented in a structure that is often tabular (represented by rows and columns), a tree (a set of nodes with parent- children relationship), or a graph (a set of connected nodes).
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Being a relatively new color space and having very specific uses, TSL hasn’t been widely implemented. Again, it is only very useful in skin detection algorithms. Skin detection itself can be used for a variety of applications – face detection, person tracking (for surveillance and cinematographic purposes), and pornography filtering are a few examples. A Self-Organizing Map (SOM) was implemented in skin detection using TSL and achieved comparable results to older methods of histograms and Gaussian mixture models.
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To account for changes in illumination and contrast, the gradient strengths must be locally normalized, which requires grouping the cells together into larger, spatially connected blocks. The HOG descriptor is then the concatenated vector of the components of the normalized cell histograms from all of the block regions. These blocks typically overlap, meaning that each cell contributes more than once to the final descriptor. Two main block geometries exist: rectangular R-HOG blocks and circular C-HOG blocks.
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In 1626, Christoph Scheiner published the Rosa Ursina sive Sol, a book that revealed his research about the rotation of the sun. Infographics appeared in the form of illustrations demonstrating the Sun's rotation patterns. In 1786, William Playfair, an engineer and political economist, published the first data graphs in his book The Commercial and Political Atlas. To represent the economy of 18th Century England, Playfair used statistical graphs, bar charts, line graphs, area charts, and histograms.
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Abstract Interfaces for Data Analysis (AIDA) is a set of defined interfaces and formats for representing common data analysis objects. The project was instigated and is primarily used by researchers in high-energy particle physics. As of 2011, the projects seems dormant, with last "recent news" on the project homepage dating from 2005. The goals of the AIDA project are to define abstract interfaces for common physics analysis objects, such as histograms, ntuples (or data trees), fitters, I/O etc.
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Histograms are nevertheless preferred in applications, when their statistical properties need to be modeled. The correlated variation of a kernel density estimate is very difficult to describe mathematically, while it is simple for a histogram where each bin varies independently. An alternative to kernel density estimation is the average shifted histogram, which is fast to compute and gives a smooth curve estimate of the density without using kernels. The histogram is one of the seven basic tools of quality control.
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These data are often plotted as brightness-area histograms for a particular time or, in a 3-3-dimensional display, showing a time sequence of changing intensity of optical emissions from areas of solar active regions. The automatic capability of the SOON telescope system allows the rapid collection of this brightness-area information on many active regions on the sun. By using these data, quantitative measures can be determined, include instability, growth/decay rates, and precise dimensions for each active solar region.
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In most cases palette change is better as it preserves the original data. Modifications of this method use multiple histograms, called subhistograms, to emphasize local contrast, rather than overall contrast. Examples of such methods include adaptive histogram equalization, contrast limiting adaptive histogram equalization or CLAHE, multipeak histogram equalization (MPHE), and multipurpose beta optimized bihistogram equalization (MBOBHE). The goal of these methods, especially MBOBHE, is to improve the contrast without producing brightness mean-shift and detail loss artifacts by modifying the HE algorithm.
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Histograms of a synthetic red giant population (in red) and CoRoT red giant population (in orange). From Andrea Miglio and collaborators 3D map of our galaxy from seismic data of red giants observed by CoRoT. From Andrea Miglio and collaborators Whether RGB or RC, these stars all have an extended convective envelope favorable to the excitation of solar-like oscillations. A major success of CoRoT has been the discovery of radial and long-lived non-radial oscillations in thousands of red giants in the exo field.
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Previous steps found keypoint locations at particular scales and assigned orientations to them. This ensured invariance to image location, scale and rotation. Now we want to compute a descriptor vector for each keypoint such that the descriptor is highly distinctive and partially invariant to the remaining variations such as illumination, 3D viewpoint, etc. This step is performed on the image closest in scale to the keypoint's scale. First a set of orientation histograms is created on 4×4 pixel neighborhoods with 8 bins each.
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These histograms are computed from magnitude and orientation values of samples in a 16×16 region around the keypoint such that each histogram contains samples from a 4×4 subregion of the original neighborhood region. The image gradient magnitudes and orientations are sampled around the keypoint location, using the scale of the keypoint to select the level of Gaussian blur for the image. In order to achieve orientation invariance, the coordinates of the descriptor and the gradient orientations are rotated relative to the keypoint orientation.
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The system was designed to use as little computer memory as possible. At any given X location it could draw two dots at given Y locations, making it suitable for producing two superimposed waveforms, line charts or histograms. Text and graphics could be mixed, and there were additional tools for drawing axes and markers. The waveform graphics system was used only for a short period of time before it was replaced by the more sophisticated ReGIS system, first introduced on the VT125 in 1981.
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A simple stem plot may refer to plotting a matrix of y values onto a common x axis, and identifying the common x value with a vertical line, and the individual y values with symbols on the line.Examples: MATLAB's and Matplotlib's stem functions. They do not create a stem-and-leaf display. Unlike histograms, stem-and-leaf displays retain the original data to at least two significant digits, and put the data in order, thereby easing the move to order-based inference and non-parametric statistics.
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Galton invented the use of the regression line and for the choice of r (for reversion or regression) to represent the correlation coefficient. In the 1870s and 1880s he was a pioneer in the use of normal theory to fit histograms and ogives to actual tabulated data, much of which he collected himself: for instance large samples of sibling and parental height. Consideration of the results from these empirical studies led to his further insights into evolution, natural selection, and regression to the mean.
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Graphics Layout Engine (GLE) is a graphics scripting language designed for creating publication quality graphs, plots, diagrams, figures and slides. GLE supports various graph types such as function plots, histograms, bar graphs, scatter plots, contour lines, color maps and surface plots through a simple but flexible set of graphing commands. More complex output can be created by relying on GLE's scripting language, which is full featured with subroutines, variables, and logic control. GLE relies on LaTeX for text output and supports mathematical formula in graphs and figures.
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Microsoft Excel has the basic features of all spreadsheets, using a grid of cells arranged in numbered rows and letter- named columns to organize data manipulations like arithmetic operations. It has a battery of supplied functions to answer statistical, engineering, and financial needs. In addition, it can display data as line graphs, histograms and charts, and with a very limited three-dimensional graphical display. It allows sectioning of data to view its dependencies on various factors for different perspectives (using pivot tables and the scenario manager).
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The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method is similar to that of edge orientation histograms, scale-invariant feature transform descriptors, and shape contexts, but differs in that it is computed on a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy. Robert K. McConnell of Wayland Research Inc.
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An early application of the EMD in computer science was to compare two grayscale images that may differ due to dithering, blurring, or local deformations. In this case, the region is the image's domain, and the total amount of light (or ink) is the "dirt" to be rearranged. The EMD is widely used in content-based image retrieval to compute distances between the color histograms of two digital images. In this case, the region is the RGB color cube, and each image pixel is a parcel of "dirt".
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In character recognition, features may include histograms counting the number of black pixels along horizontal and vertical directions, number of internal holes, stroke detection and many others. In speech recognition, features for recognizing phonemes can include noise ratios, length of sounds, relative power, filter matches and many others. In spam detection algorithms, features may include the presence or absence of certain email headers, the email structure, the language, the frequency of specific terms, the grammatical correctness of the text. In computer vision, there are a large number of possible features, such as edges and objects.
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Histograms of this energy content showed heavy- tailed properties. In some scenarios, the vast majority of events had a negligible amount of energy within the filter bandwidth (i.e., below the measurement noise floor), while a small number of events had energies at least 30–40 times the average value, making them very clearly visible. The analogy between these extreme optical events and hydrodynamic rogue waves was initially developed by noting a number of parallels, including the role of solitons, heavy-tailed statistics, dispersion, modulation instability, and frequency downshifting effects.
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Another possibility is to present survey results by means of statistical models in the form of a multivariate distribution mixture. The statistical information in the form of conditional distributions (histograms) can be derived interactively from the estimated mixture model without any further access to the original database. As the final product does not contain any protected microdata, the model-based interactive software can be distributed without any confidentiality concerns. Another method is simply to release no data at all, except very large scale data directly to the central government.
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This means that when the user has multiple views or windows in a project, selecting an object in one of them will highlight the same object in all other windows. GeoDa also is capable of producing histograms, box plots, Scatter plots to conduct simple exploratory analyses of the data. The most important thing, however, is the capability of mapping and linking those statistical devices with the spatial distribution of the phenomenon that the users are studying. Multivariate ESDA: multiple views linked to explore the relations in various characteristics of Colombian municipalities.
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A utilization distribution is a probability distribution giving the probability density that an animal is found at a given point in space. It is estimated from data sampling the location of an individual or individuals in space over a period of time using, for example, telemetry or GPS based methods. Estimation of utilization distribution was traditionally based on histograms but newer nonparametric methods based on Fourier transformations , kernel density and local convex hull methods have been developed. The typical application for this distribution is estimating the home range distribution of animals.
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Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization in the respect that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image. It is therefore suitable for improving the local contrast and enhancing the definitions of edges in each region of an image. However, AHE has a tendency to overamplify noise in relatively homogeneous regions of an image.
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Computer Graphics and Image Processing 6 (1977) 184195. In its simplest form, each pixel is transformed based on the histogram of a square surrounding the pixel, as in the figure below. The derivation of the transformation functions from the histograms is exactly the same as for ordinary histogram equalization: The transformation function is proportional to the cumulative distribution function (CDF) of pixel values in the neighbourhood. 300 px Pixels near the image boundary have to be treated specially, because their neighbourhood would not lie completely within the image.
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The result of summing these kernels is given on the right figure, which is a kernel density estimate. The most striking difference between kernel density estimates and histograms is that the former are easier to interpret since they do not contain artifices induced by a binning grid. The coloured contours correspond to the smallest region which contains the respective probability mass: red = 25%, orange + red = 50%, yellow + orange + red = 75%, thus indicating that a single central region contains the highest density. Construction of 2D kernel density estimate. Left.
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Lertap5 (the 5th version of the Laboratory of Educational Research Test Analysis Program) is a comprehensive software package for classical test analysis developed for use on Windows and Macintosh computers with Microsoft Excel. It includes test, item, and option statistics, classification consistency and mastery test analysis, procedures for cheating detection, and extensive graphics (e.g., trace lines for item options, conditional standard errors of measurement, scree plots, boxplots of group differences, histograms, scatterplots). DIF, differential item functioning, is supported in the Excel 2010, Excel 2013, Excel 2016, and Excel 2019 versions of Lertap5.
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Graph made using Microsoft Excel Excel supports charts, graphs, or histograms generated from specified groups of cells. The generated graphic component can either be embedded within the current sheet or added as a separate object. These displays are dynamically updated if the content of cells changes. For example, suppose that the important design requirements are displayed visually; then, in response to a user's change in trial values for parameters, the curves describing the design change shape, and their points of intersection shift, assisting the selection of the best design.
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Such abundance classes are called octaves; early developers of this concept included F. W. Preston and histograms showing number of species as a function of abundance octave are known as Preston diagrams. These bins are not mutually exclusive: a species with abundance 4, for example, could be considered as lying in the 2-4 abundance class or the 4-8 abundance class. Species with an abundance of an exact power of 2 (i.e. 2,4,8,16, etc.) are conventionally considered as having 50% membership in the lower abundance class 50% membership in the upper class.
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The most basic histogram is the equi-width histogram, where each bucket represents the same range of values. That histogram would be defined as having a Sort Value of Value, a Source Value of Frequency, be in the Serial Partition Class and have a Partition Rule stating that all buckets have the same range. V-optimal histograms are an example of a more "exotic" histogram. V-optimality is a Partition Rule which states that the bucket boundaries are to be placed as to minimize the cumulative weighted variance of the buckets.
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The second step of calculation is creating the cell histograms. Each pixel within the cell casts a weighted vote for an orientation-based histogram channel based on the values found in the gradient computation. The cells themselves can either be rectangular or radial in shape, and the histogram channels are evenly spread over 0 to 180 degrees or 0 to 360 degrees, depending on whether the gradient is “unsigned” or “signed”. Dalal and Triggs found that unsigned gradients used in conjunction with 9 histogram channels performed best in their human detection experiments.
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This statistical approach creates multiple, equi-probable models consistent with the seismic, wells, and geology. Geostatistical inversion simultaneously inverts for impedance and discrete properties types, and other petrophysical properties such as porosity can then be jointly cosimulated. The output volumes are at a sample rate consistent with the reservoir model because making synthetics of finely sampled models is the same as from well logs. Inversion properties are consistent with well log properties because the histograms used to generate the output rock properties from the inversion are based on well log values for those rock properties.
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Extensions of the SIFT descriptor to 2+1-dimensional spatio-temporal data in context of human action recognition in video sequences have been studied. The computation of local position-dependent histograms in the 2D SIFT algorithm are extended from two to three dimensions to describe SIFT features in a spatio-temporal domain. For application to human action recognition in a video sequence, sampling of the training videos is carried out either at spatio-temporal interest points or at randomly determined locations, times and scales. The spatio-temporal regions around these interest points are then described using the 3D SIFT descriptor.
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CHICOS has a data collection system that is recording all the large cosmic ray showers that fall within the array. The information that is collected from the Cosmic Ray detectors from different schools are combined to reconstruct cosmic ray events. These events are analyzed to create histograms of cosmic ray incidents, including a sky-map that would indicate the spread of cosmic rays directions from outer space, with each shower that is recorded indicating a cosmic event. The goal of CHICOS is to be able to trace these cosmic rays back to their source, and understand what it exactly is that produces UHECRs.
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Brest and Rossow [1992], and the updated methodology [Brest et al., 1997], put forth a robust method for calibration monitoring of individual sensors and normalization of all sensors to a common standard. The International Satellite Cloud Climatology Project (ISCCP) method begins with the detection of clouds and corrections for ozone, Rayleigh scatter, and seasonal variations in irradiance to produce surface reflectances. Monthly histograms of surface reflectance are then produced for various surface types, and various histogram limits are then applied as a filter to the original sensor observations and ultimately aggregated to produce a global, cloud free surface reflectance.
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This software provides a comprehensive set of capabilities including frequencies, cross-tabs comparison of means (t-tests and one-way ANOVA), linear regression, logistic regression, reliability (Cronbach's alpha, not failure or Weibull), and re-ordering data, non- parametric tests, factor analysis, cluster analysis, principal components analysis, chi-square analysis and more. At the user's choice, statistical output and graphics are available in ASCII, PDF, PostScript, SVG or HTML formats. A range of statistical graphs can be produced, such as histograms, pie-charts, scree plots, and np-charts. PSPP can import Gnumeric and OpenDocument spreadsheets, Postgres databases, comma-separated values and ASCII files.
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Fluorescence signal is detected either using ultra sensitive CCD or scientific CMOS cameras for wide field microscopy or SPADs for confocal microscopy. Once the single molecule intensities vs. time are available the FRET efficiency can be computed for each FRET pair as a function of time and thereby it is possible to follow kinetic events on the single molecule scale and to build FRET histograms showing the distribution of states in each molecule. However, data from many FRET pairs must be recorded and combined in order to obtain general information about a sample or a dynamic structure.
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On public display in downtown Mountain View, California, as part of NASA Ames' 75th anniversary. X-ray diffraction view of the Martian soil - CheMin analysis reveals feldspar, pyroxenes, olivine and more (Curiosity rover, "Rocknest", October 17, 2012). CheMin is an X-ray powder diffraction instrument that also has X-ray fluorescence capabilities. CheMin does not require the use of liquid reagents, instead, it utilizes a microfocus cobalt X-ray source, a transmission sample cell and an energy-discriminating X-ray sensitive CCD to produce simultaneous 2-D X-ray diffraction patterns and energy-dispersive histograms from powdered samples.
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This is necessary when performing node segmentation at the object level. Time introduces complexity in this case also, for even after an object is differentiated in one frame, it is usually necessary to follow the same object through a sequence of frames. This process, known as object tracking, is essential to the creation of links from objects in videos. Spatial segmentation of object can be achieved, for example, through the use of intensity gradients to detect edges, color histograms to match regions, Smith, Jason and Stotts, David, An Extensible Object Tracking Architecture for Hyperlinking in Real-time and Stored Video Streams, Dept.
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A Q–Q plot is used to compare the shapes of distributions, providing a graphical view of how properties such as location, scale, and skewness are similar or different in the two distributions. Q–Q plots can be used to compare collections of data, or theoretical distributions. The use of Q–Q plots to compare two samples of data can be viewed as a non-parametric approach to comparing their underlying distributions. A Q–Q plot is generally a more powerful approach to do this than the common technique of comparing histograms of the two samples, but requires more skill to interpret.
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The timing electronics is needed to losslessly reconstruct the histogram of the distribution of time of flight of photons. This is done by using the technique of time-correlated single photon counting (TCSPC), where the individual photon arrival times are marked with respect to a start/stop signal provided by the periodic laser cycle. These time-stamps can then be used to build up histograms of photon arrival times. The two main types of timing electronics are based on a combination of time-to-analog converter (TAC) and an analog-to-digital converter (ADC), and time-to-digital converter (TDC), respectively.
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Detectors are trained to search for pedestrians in the video frame by scanning the whole frame. The detector would “fire” if the image features inside the local search window meet certain criteria. Some methods employ global features such as edge template ,C. Papageorgiou and T. Poggio, "A Trainable Pedestrian Detection system", International Journal of Computer Vision (IJCV), pages 1:15–33, 2000 others uses local features like histogram of oriented gradients N. Dalal, B. Triggs, “Histograms of oriented gradients for human detection”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 1:886–893, 2005 descriptors.
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The hierarchical shape and appearance model for human action introduces a new part layer (Constellation model) between the mixture proportion and the BoW features, which captures the spatial relationships among parts in the layer. For discriminative models, spatial pyramid match performs pyramid matching by partitioning the image into increasingly fine sub-regions and compute histograms of local features inside each sub-region. Recently, an augmentation of local image descriptors (i.e. SIFT) by their spatial coordinates normalised by the image width and height have proved to be a robust and simple Spatial Coordinate Coding approach which introduces spatial information to the BoW model.
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Players are generally free to write code for EXAs with as many EXAs as necessary, those are often limited by the number of opcodes that can be used. The player's solution must satisfy 100 different case scenarios iterating on the same problem. When the player demonstrates a successful solution, the game records how many cycles the solution took, the size of their code across all EXAs, and the number of movement and kill commands executed by the solution. These are tracked against other players' scores via histograms and friends' scoreboards, allowing players to try to optimize their solutions.
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All field data is incorporated into the geostatistical inversion process through the use of probability distribution functions (PDFs). Each PDF describes a particular input data in geostatistical terms using histograms and variograms, which identify the odds of a given value at a specific place and the overall expected scale and texture based on geologic insight. Once constructed, the PDFs are combined using Bayesian inference, resulting in a posterior PDF that conforms to everything that is known about the field."Incorporating Geophysics into Geologic Models: New Approach Makes Geophysical Models Available to Engineers in a Form They Can Use", Fugro-Jason White Paper, 2008.
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Geostatistical inversion integrates data from many sources and creates models that have greater resolution than the original seismic, match known geological patterns, and can be used for risk assessment and reduction. Seismic, well logs and other input data are each represented as a probability density function (PDF), which provides a geostatistical description based on histograms and variograms. Together these define the chances of a particular value at a particular location, and the expected geological scale and composition throughout the modeled area. Unlike conventional inversion and geomodeling algorithms, geostatistical inversion takes a one-step approach, solving for impedance and discrete property types or lithofacies at the same time.
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Xiang-Yang Wang, Jun-Feng Wu, and Hong-Ying Yang "Robust image retrieval based on color histogram of local feature regions" Springer Netherlands, 2009 ISSN 1573-7721 Some of the proposed solutions have been color histogram intersection, color constant indexing, cumulative color histogram, quadratic distance, and color correlograms. Although there are drawbacks of using histograms for indexing and classification, using color in a real-time system has several advantages. One is that color information is faster to compute compared to other invariants. It has been shown in some cases that color can be an efficient method for identifying objects of known location and appearance.
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" The Hindu's G. Sampath wrote, "Contradicting the claims of Hayekian market fundamentalists, Piketty shows, through page after page of charts, graphs and histograms, how unfettered capitalism in 19th century Europe led to levels of inequality not seen anywhere except in quasi- slave societies. [...] The singular value of this book may well be its power to revive research and activism that re-embed economic problems in a social and civic substrate." The New Republic's Robin Kaiser-Schatzlein argued, "Piketty’s own imagination of new worlds is grounded in a rigorous and detailed analysis of the institutions that have existed in the real world. [...] He is uncovering ideas that have worked before.
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While serving as nurse during the Crimean War, Florence Nightingale drew the first pie charts representing the monthly fatality rates of the conflict, distinguishing deaths due to battle wounds (innermost section), those due to infectious disease (outer section), and to other causes (middle section). (See figure.) Her charts clearly showed that most deaths resulted from disease, which led the general public to demand improved sanitation at field hospitals. Although bar charts representing frequencies were first used by the Frenchman A. M. Guerry in 1833, it was the statistician Karl Pearson who gave them the name histograms. Pearson used them in an 1895 article mathematically analyzing biological evolution.
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Effectiveness estimation of image retrieval by 2D color histogram; Bashkov, E.A.; Kostyukova, N.S.; Journal of Automation and Information Sciences, 2006 (6) Page(s): 84-89 A two-dimensional color histogram is a two- dimensional array. The size of each dimension is the number of colors that were used in the phase of color quantization. These arrays are treated as matrices, each element of which stores a normalized count of pixel pairs, with each color corresponding to the index of an element in each pixel neighborhood. For comparison of two-dimensional color histograms it is suggested calculating their correlation, because constructed as described above, is a random vector (in other words, a multi-dimensional random value).
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Fyre, formerly de Jong Explorer, is a cross-platform tool for producing artwork based on histograms of iterated chaotic functions. It implements the Peter de Jong map in a fixed function pipeline through either a GTK GUI frontend, or a command line facility for easier rendering of high-resolution, high quality images. The program was renamed from de Jong Explorer to Fyre simply because 'It wasn't taken yet' and so that in the future, it could support more functions than just the standard Peter de Jong map. Fyre features a sidebar on the left to which the user can input the required variables and on the right is displayed the result of the equation.
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Histograms are an example of data binning used in order to observe underlying distributions. They typically occur in one-dimensional space and in equal intervals for ease of visualization. Data binning may be used when small instrumental shifts in the spectral dimension from mass spectrometry (MS) or nuclear magnetic resonance (NMR) experiments will be falsely interpreted as representing different components, when a collection of data profiles is subjected to pattern recognition analysis. A straightforward way to cope with this problem is by using binning techniques in which the spectrum is reduced in resolution to a sufficient degree to ensure that a given peak remains in its bin despite small spectral shifts between analyses.
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ISO may then be increased to bring the image up to a desired brightness. But, since increasing ISO does not actually increase sensor exposure (instead the sensor's signal gain is increased), it should be applied only after the actual exposure (set by the f-ratio and shutter speed) has been made as large as possible subject to shooting constraints. Live histograms and highlight-clipping indicators, which are almost always based on the processed JPEG rather than on the raw data, might indicate highlights are blown when in fact they are not and could be recoverable from a raw file. Therefore, it can be difficult to expose properly to the right without risking inadvertently blown highlights.
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It is scriptable using Qt Script for Applications (QSA). 2D and 3D plots of data can be rendered in a "worksheet", either by directly reading datafiles or from a spreadsheet, which LabPlot supports. It has interfaces to several libraries, including GSL for data analysis, the Qwt3d libraries for 3D plotting using OpenGL, FFTW for fast Fourier transforms and supports exporting to 80 image formats and raw PostScript. Other key features include live data plotting, support for the FITS format, for LaTeX and Rich Text labels, data masking, data picking from images, multiple plots in the same worksheet, pie charts, bar charts/histograms, interpolation, data smoothing, peak fitting, nonlinear curve fitting, regression, deconvolution, integral transforms, and others (see developers website listed below for details).
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All birds with established breeding populations within Europe are covered in a single-page or two-page account which includes a map of breeding distribution, histograms showing those countries with the largest breeding populations, and a species text. Seventeen further species for which some breeding behaviour has been observed within the region are covered more briefly. Some species distributions are shown on maps of the whole survey area, but for those with more restricted distributions, base maps showing only a relevant subdivision are shown. The book concludes with sections on the Conservation Status of Europe's Birds, a list of species with threat statuses, a set of derived maps depicting overall species richness and richness of threatened species, and a 65-page references section.
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Frankel is a strong advocate of image integrity for scientific and documentary photographic images. She also recommends appropriate use of image adjustment and enhancement techniques such as color enhancement, grayscale inversion, or selective deletion of distracting or irrelevant elements, as well as more subtle manipulations of image histograms, all in service of goals such as clarity of communication. However, she insists that all image manipulation must be fully disclosed, to avoid misleading the reader regarding the integrity of the scientific images. In her 2018 book, Frankel has reprinted the journal publication guidelines of Nature, Science, and Cell, comparing the extensively detailed directives of the first journal with the minimal guidance given in the latter two publications as of her book's publication deadline.
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Traditional ways of managing sales people did not work when team members who had to develop a new way of selling were embedded in 14 different sales offices around the US. The culture of sales was based on intuition and gut feel, not on data and mathematical logic like the culture of operational excellence. However, many people inside the quality movement could see that the scientific mindset ought to apply to sales and marketing. Paul Selden's "Sales Process Engineering, A Personal Workshop" was a further attempt to demonstrate the applicability of the theory and tools of quality management to the sales function. The book applied Deming's 14 Points and the tools of quality measurement (such as check sheets, run charts, histograms, etc.), in a sales context.
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In register zero, bit 0 (least significant) turned the entire line drawing system on or off. Bits 1 and 2 turned the individual graphs 0 or 1 on or off, and bits 3 and 4 controlled whether graphs 0 and 1 were lines or filled in to make histograms. For instance, if one wanted to have both graphs on-screen, but graph 0 would be a histogram and graph 1 would be a line, the required bit pattern would be 0101111, the leading 01 being fixed, the next bit saying graph 1 is a line (0), the next that graph 0 is a histogram (1), that both graphs are on (11) and that the entire graphics system is enabled (1).
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The utilization of Globally Unique Identifiers (GUID) to represent each element in the file permits the format to be extensible without the need for a central registration authority. PQDIF allows storage of the following types of measurements: waveforms, time series value logs (rms voltage, rms current, real/reactive/apparent power, total harmonic distortion, harmonics, flicker, etc.), phasors, frequency spectrums, lightning strikes, histograms, cross- tabulations, and magnitude-duration summary tables for voltage sags, voltage swells, interruptions, transients and rapid voltage changes. PQDIF allows storage of information related to the sources that recorded the data, including name, description, location, transducer settings, trigger settings, and more. A single PQDIF file is a collection of PQDIF records consisting of a Container record, Data Source record, an optional Monitor Settings record, and one or more Observation records.
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Zachtronics' games have generally been focused around engineering puzzle games, designing machines or the equivalent to take input and make output; these are generally part of the broader class of programming games. These games, including SpaceChem, Infinifactory, and Opus Magnum, feature multiple puzzles that are open ended in solution; as long as the player can make the required output, the game considers that puzzle solved and allows the player to access the next puzzle. Atop their solution, the player is shown statistics related to their solution which relate to some efficiency - how fast their solution completed the puzzle, how few parts they used, and the like. These stats are given with histograms from other players, including their friends via the game's storefront, that have also completed that puzzle.
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In some cases, Barth discovered that players made assumptions on limitations of the game from these tutorials such as the idea that the red and blue waldos must remain in the separate halves of the screen. Based on the feedback that players had made on sites that hosted his previous Flash-based games, Barth designed the global-based histograms to allow players to check their solution without feeling overwhelmed by the top players as would be normally listed on a leaderboard. He also devised the means of sharing solutions through YouTube videos due to similar comments and discussions on the previous games. Barth had envisioned the game as his first commercial project, and based on feedback from Codex and other games, wanted to include a storyline along with the puzzles.
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CodedColor PhotoStudio is a photo organizer and image editing software for digital camera users. The software comes with a handbook and a database to store Exif / IPTC data and color informationen. The interface includes features like photo editing & printing, web album galleries, slide shows, photo management & cataloging, custom sorting, IPTC & Exif editor, thumbnail generation, resize & resample images, jp2000, batch conversion, database keyword searching, red eye removal, color / sharpness / brightness & contrast correction, artefacts removal, clone brush, scanner & TWAIN import, screen capture, lossless JPEG rotation, gamma correction, print ordering and screenshows with many transition effects, watermark text, image annotations, panorama stitch & animation, video capture, PDF album export, photo layouts, collages, frames, shadows, histograms, automatic white balance, and Skype photo sharing. You can also rename multiple images, remove scratches, create panorama pictures (stitch), convert RAW photos (from Canon, Nikon, Olympus, etc.
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Statistics were introduced into the Hutchinson niche by Robert MacArthur and Richard Levins using the 'resource-utilization' niche employing histograms to describe the 'frequency of occurrence' as a function of a Hutchinson coordinate. So, for instance, a Gaussian might describe the frequency with which a species ate prey of a certain size, giving a more detailed niche description than simply specifying some median or average prey size. For such a bell-shaped distribution, the position, width and form of the niche correspond to the mean, standard deviation and the actual distribution itself. One advantage in using statistics is illustrated in the figure, where it is clear that for the narrower distributions (top) there is no competition for prey between the extreme left and extreme right species, while for the broader distribution (bottom), niche overlap indicates competition can occur between all species.
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In statistics, the earth mover's distance (EMD) is a measure of the distance between two probability distributions over a region D. In mathematics, this is known as the Wasserstein metric. Informally, if the distributions are interpreted as two different ways of piling up a certain amount of dirt over the region D, the EMD is the minimum cost of turning one pile into the other; where the cost is assumed to be amount of dirt moved times the distance by which it is moved.Formal definition The above definition is valid only if the two distributions have the same integral (informally, if the two piles have the same amount of dirt), as in normalized histograms or probability density functions. In that case, the EMD is equivalent to the 1st Mallows distance or 1st Wasserstein distance between the two distributions.
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Furthermore, the scale levels obtained from automatic scale selection can be used for determining regions of interest for subsequent affine shape adaptation to obtain affine invariant interest points or for determining scale levels for computing associated image descriptors, such as locally scale adapted N-jets. Recent work has shown that also more complex operations, such as scale- invariant object recognition can be performed in this way, by computing local image descriptors (N-jets or local histograms of gradient directions) at scale-adapted interest points obtained from scale-space extrema of the normalized Laplacian operator (see also scale-invariant feature transform) or the determinant of the Hessian (see also SURF); see also the Scholarpedia article on the scale-invariant feature transform for a more general outlook of object recognition approaches based on receptive field responses in terms Gaussian derivative operators or approximations thereof.
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Figure 2: Graph showing histograms of person distribution (top) and item distribution (bottom) on a scale For dichotomous data such as right/wrong answers, by definition, the location of an item on a scale corresponds with the person location at which there is a 0.5 probability of a correct response to the question. In general, the probability of a person responding correctly to a question with difficulty lower than that person's location is greater than 0.5, while the probability of responding correctly to a question with difficulty greater than the person's location is less than 0.5. The Item Characteristic Curve (ICC) or Item Response Function (IRF) shows the probability of a correct response as a function of the ability of persons. A single ICC is shown and explained in more detail in relation to Figure 4 in this article (see also the item response function).
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The following example will construct a V-optimal histogram having a Sort Value of Value, a Source Value of Frequency, and a Partition Class of Serial. In practice, almost all histograms used in research or commercial products are of the Serial class, meaning that sequential sort values are placed in either the same bucket, or sequential buckets. For example, values 1, 2, 3 and 4 will be in buckets 1 and 2, or buckets 1, 2 and 3, but never in buckets 1 and 3. That will be taken as an assumption in any further discussion. Take a simple set of data, for example, a list of integers: 1, 3, 4, 7, 2, 8, 3, 6, 3, 6, 8, 2, 1, 6, 3, 5, 3, 4, 7, 2, 6, 7, 2 Compute the value and frequency pairs (1, 2), (2, 4), (3, 5), (4, 2), (5, 1), (6, 4), (7, 3), (8, 2) Our V-optimal histogram will have two buckets.
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In the domain of physics and probability, the filters, random fields, and maximum entropy (FRAME) model is a Markov random field model (or a Gibbs distribution) of stationary spatial processes, in which the energy function is the sum of translation-invariant potential functions that are one-dimensional non-linear transformations of linear filter responses. The FRAME model was originally developed by Song-Chun Zhu, Ying Nian Wu, and David Mumford for modeling stochastic texture patterns, such as grasses, tree leaves, brick walls, water waves, etc. This model is the maximum entropy distribution that reproduces the observed marginal histograms of responses from a bank of filters (such as Gabor filters or Gabor wavelets), where for each filter tuned to a specific scale and orientation, the marginal histogram is pooled over all the pixels in the image domain. The FRAME model is also proved to be equivalent to the micro-canonical ensemble , which was named the Julesz ensemble.
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However, it has long been noted that a neural mechanism that may accomplish a delay—a necessary operation of a true autocorrelation—has not been found. At least one model shows that a temporal delay is unnecessary to produce an autocorrelation model of pitch perception, appealing to phase shifts between cochlear filters; however, earlier work has shown that certain sounds with a prominent peak in their autocorrelation function do not elicit a corresponding pitch percept, and that certain sounds without a peak in their autocorrelation function nevertheless elicit a pitch. To be a more complete model, autocorrelation must therefore apply to signals that represent the output of the cochlea, as via auditory-nerve interspike-interval histograms. Some theories of pitch perception hold that pitch has inherent octave ambiguities, and therefore is best decomposed into a pitch chroma, a periodic value around the octave, like the note names in western music—and a pitch height, which may be ambiguous, that indicates the octave the pitch is in.
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The imprinted image turned out to be wash-resistant, impervious to temperatures of and was undamaged by exposure to a range of harsh chemicals, including bisulphite which, without the gelatine, would normally have degraded ferric oxide to the compound ferrous oxide. Instead of painting, it has been suggested that the bas-relief could also be heated and used to scorch an image onto the cloth. However researcher Thibault Heimburger performed some experiments with the scorching of linen, and found that a scorch mark is only produced by direct contact with the hot object—thus producing an all-or- nothing discoloration with no graduation of color as is found in the shroud. According to Fanti and Moroni, after comparing the histograms of 256 different grey levels, it was found that the image obtained with a bas-relief has grey values included between 60 and 256 levels, but it is much contrasted with wide areas of white saturation (levels included between 245 and 256) and lacks of intermediate grey levels (levels included between 160 and 200).
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In some cases, storefronts and aggregates have intervened to stop review bombs and delete the negative reviews. In February 2019, Rotten Tomatoes announced that it would no longer accept user reviews for a film until after its official release. Valve added review histograms to Steam user review scores to show how these change over time; according to Valve's Alden Kroll, this can help a potential purchaser of a game recognize a short term review bomb that is not indicative of the game itself, compared to a game that has a long tail of bad reviews. Kroll said they did not want to silence the ability of users to leave reviews but recognized they needed to highlight phenomena like review bombs to aid consumers. In March 2019, Valve stated that it would employ a new system to detect spikes of negative "off-topic" reviews on games: if it is determined that they were the result of a review bomb campaign, the time period will be flagged, and all reviews made during that period (whether negative or positive) will be excluded them from the user rating displayed for a game.
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