— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Given the spectral difference between speech and acoustic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature componen...
Xi Zhou, Xiaodan Zhuang, Ming Liu, Hao Tang, Mark ...
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimizatio...
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...