Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a nov...
Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
This paper presents a theoretically very simple yet efficient approach for gray scale and rotation invariant texture classification based on local binary patterns and nonparametric...
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly m...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...