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Products. Paragliders. Website. www .gradient .cx. Gradient sro is a Czech aircraft manufacturer based in Prague and founded in 1997. The company specializes in the design and manufacture of paragliders in the form of ready-to-fly aircraft. [1] [2] The company is organized as a společnost s ručením omezeným (sro), a Czech private limited ...
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 ...
Mechanically gradient polymers. Polymer gradient materials (PGM) are a class of polymers with gradually changing mechanical properties along a defined direction creating an anisotropic material. These materials can be defined based upon the direction and the steepness of the gradient used and can display gradient or graded transitions. [1]
GNU Image Manipulation Program, commonly known by its acronym GIMP (/ ɡ ɪ m p / GHIMP), is a free and open-source raster graphics editor [4] used for image manipulation (retouching) and image editing, free-form drawing, transcoding between different image file formats, and more specialized tasks.
Type of aircraft. National origin. Czech Republic. Manufacturer. Gradient sro. Status. In production (Bright 5, 2016) The Gradient Bright is a Czech single-place, paraglider designed and produced by Gradient sro of Prague. Originally produced in the mid-2000s, it was still in production in 2016 as the Bright 5.
Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals rather than the typical residuals used in traditional boosting. It gives a prediction model in the form of an ensemble of weak prediction models, i.e., models that make very few assumptions about the data, which are ...
Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate function. The idea is to take repeated steps in the opposite direction of the gradient (or approximate gradient) of the function at the current point, because this is the direction of ...
In orthogonal curvilinear coordinates of 3 dimensions, where = ; = = one can express the gradient of a scalar or vector field as = = = ; = For an orthogonal basis = = = The divergence of a vector field can then be written as = ( ) Also, = = = ; = = ; = = Therefore, = ( ) We can get an expression for the Laplacian in a similar manner by noting ...