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  2. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

  3. Generalised Hough transform - Wikipedia

    en.wikipedia.org/wiki/Generalised_Hough_transform

    The generalized Hough transform (GHT), introduced by Dana H. Ballard in 1981, is the modification of the Hough transform using the principle of template matching. [1] The Hough transform was initially developed to detect analytically defined shapes (e.g., line, circle, ellipse etc.). In these cases, we have knowledge of the shape and aim to ...

  4. Circle Hough Transform - Wikipedia

    en.wikipedia.org/wiki/Circle_Hough_Transform

    The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix. It is a specialization of the Hough transform.

  5. Gradient method - Wikipedia

    en.wikipedia.org/wiki/Gradient_method

    In optimization, a gradient method is an algorithm to solve problems of the form min x ∈ R n f ( x ) {\displaystyle \min _{x\in \mathbb {R} ^{n}}\;f(x)} with the search directions defined by the gradient of the function at the current point.

  6. Category:Gradient methods - Wikipedia

    en.wikipedia.org/wiki/Category:Gradient_methods

    Pages in category "Gradient methods" The following 20 pages are in this category, out of 20 total. This list may not reflect recent changes. ...

  7. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    The gradient region is sampled at 39×39 locations, therefore the vector is of dimension 3042. The dimension is reduced to 36 with PCA. Gradient location-orientation histogram is an extension of the SIFT descriptor designed to increase its robustness and distinctiveness. The SIFT descriptor is computed for a log-polar location grid with three ...

  8. Template:Linear-gradient background - Wikipedia

    en.wikipedia.org/wiki/Template:Linear-gradient...

    Displays a background using multiple colors which gradually phases from one color to another. Template parameters [Edit template data] Parameter Description Type Status Background color 1 1 First background color Suggested values #000000 Line optional Background color 2 2 Second background color Suggested values #000000 Line optional Background color 3 3 Third background color Suggested values ...

  9. Boosting (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Boosting_(machine_learning)

    Orange, a free data mining software suite, module Orange.ensemble Weka is a machine learning set of tools that offers variate implementations of boosting algorithms like AdaBoost and LogitBoost R package GBM (Generalized Boosted Regression Models) implements extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting ...