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  2. Histogram of oriented gradients - Wikipedia

    en.wikipedia.org/wiki/Histogram_of_oriented...

    v. t. e. 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 ...

  3. Entropy estimation - Wikipedia

    en.wikipedia.org/wiki/Entropy_estimation

    Entropy estimation. In various science/engineering applications, such as independent component analysis, [1] image analysis, [2] genetic analysis, [3] speech recognition, [4] manifold learning, [5] and time delay estimation [6] it is useful to estimate the differential entropy of a system or process, given some observations.

  4. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Machine learningand data mining. These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning ), computer hardware, and, less ...

  5. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    Histogram equalization accomplishes this by effectively spreading out the highly populated intensity values which are used to degrade image contrast. The method is useful in images with backgrounds and foregrounds that are both bright or both dark. In particular, the method can lead to better views of bone structure in x-ray images, and to ...

  6. Balanced histogram thresholding - Wikipedia

    en.wikipedia.org/wiki/Balanced_histogram...

    In image processing, the balanced histogram thresholding method (BHT), [1] is a very simple method used for automatic image thresholding. Like Otsu's Method [2] and the Iterative Selection Thresholding Method, [3] this is a histogram based thresholding method. This approach assumes that the image is divided in two main classes: The background ...

  7. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    A histogram is a visual representation of the distribution of quantitative data. The term was first introduced by Karl Pearson. [1] To construct a histogram, the first step is to "bin" (or "bucket") the range of values— divide the entire range of values into a series of intervals—and then count how many values fall into each interval.

  8. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Regression Analysis of Time Series (RATS) – comprehensive econometric analysis package. Rguroo Statistical Software - An online statistical software designed for teaching and analyzing data. S-PLUS – general statistics package. SAS (software) – comprehensive statistical package.

  9. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    Freedman–Diaconis rule. In statistics, the Freedman–Diaconis rule can be used to select the width of the bins to be used in a histogram. [1] It is named after David A. Freedman and Persi Diaconis . For a set of empirical measurements sampled from some probability distribution, the Freedman–Diaconis rule is designed approximately minimize ...

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