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IJCNN
2008
IEEE
14 years 1 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— 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...
Tsuneyoshi Ishii, Shigeo Abe
CLEAR
2007
Springer
179views Biometrics» more  CLEAR 2007»
14 years 26 days ago
HMM-Based Acoustic Event Detection with AdaBoost Feature Selection
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 ...
CLOR
2006
13 years 10 months ago
Comparison of Generative and Discriminative Techniques for Object Detection and Classification
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...
Ilkay Ulusoy, Christopher M. Bishop
ICIP
2010
IEEE
13 years 4 months ago
Robust object detection scheme using feature selection
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...
Hong Pan, Liang-Zheng Xia, Truong Q. Nguyen
CVPR
2009
IEEE
13 years 10 months ago
Efficiently training a better visual detector with sparse eigenvectors
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 ...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...