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Global Regularizing Flows with Topology Preservation for Active Contours and Polygons
Date : 2025-07-01 Size : 1.36mb User : yasser

一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章:Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。-A semi-supervised SVM is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictionsds
Date : 2025-07-01 Size : 106kb User : 姜红茹

求解病态方程的matlab 正则化工具箱,含说明-The matlab toolbox for regularizing the ill-posed problem, including the instructions
Date : 2025-07-01 Size : 235kb User : 周宁
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