搜索资源列表
SVMScale
- Scale Data using in SVM algorithm
codeFramework
- T. Joachims, Making Large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning, B. Sch?lkopf and C. Burges and A. Smola (ed.), MIT Press, 1999.-T. Joachims, Making Large-Scale SVM Learning Practical. Advances in
fanheng
- 可以提取一幅图中想要的目标，包括最小二乘法、SVM、神经网络、1_k近邻法,结合PCA的尺度不变特征变换(SIFT)算法。- Target can be extracted in a picture you want, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Combined with PCA scale invariant feature transform (SIF
vlfeat-0.9.20.tar
- VLFeat是一个跨平台的开源机器视觉库，它囊括了当前流行的机器视觉算法，如SIFT, MSER, HOG, 同时还包含了诸如K-MEANS, Hierarchical K-means的聚类算法。它由C语言编写，并提供了Matlab接口及详细的文档。当前最新的版本是VLFeat 0.9.18 。(The VLFeat open source library implements popular computer vision algorithms specializing in image un
faoqao_v74
- SNR largest independent component analysis algorithm, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Combined with PCA scale invariant feature transform (SIFT) algorithm.