aiteam的博客

opencv是一个开源的视觉软件库，目前得到了图像和识别方面的研究者的青睐，2.2也是目前比较新的版本（opencv更新的比较快）

In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for dening the theoretically optimal, but computationally intractable, method for feature subset selection is presented. We show that our goal should be to eliminate a feature if it gives us little or no additional information beyond that subsumed by the remaining features. In particular, this will be the case for both irrelevant and redundant features. We then give an ecient algorithm for feature selection which computes an approximation to the optimal feature selection criterion. The conditions under which the approximate algorithm is successful are examined. Empirical results are given on a number of data sets, showing that the algorithm eectively handles datasets with large numbers of features.

基于信息瓶颈方法的图像分割的PPT，主要是information bottleneck method 的应用

meanshift是目标追踪中常用的算法，关于他的理论现在还没有搞懂，上传个meanshift的经典论文，大家有兴趣的一起研究，共同进步

计算机专业英语词汇下载，学习计算机英语的基础资料