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The nuclear function parameter and penalty parameter is a pivotal factor which decides performance of Least Squares Support Vector Machines (LSSVM). Common used parameters selection method for LSSVM is cross-validation, which is complicated calculation and takes a very long time. To solve these problems, a new approach based on an adaptive genetic algorithm (AGA) was proposed, which automatically...
Camera calibration is one of fundamental issues in computer vision and required for achieving accurate visual measurements. Least Squares Support Vector Machines (LS-SVM) are used to achieve the camera calibration. It doesn't need to confirm the intrinsic and extrinsic parameter of the camera. For a little more accurate calibration, acquired image is divided into two regions according to radial distortion...
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