In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
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 ...
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorith...
Antonio Robles-Kelly, Nianjun Liu, Terry Caelli, Z...