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» Learning Boosted Asymmetric Classifiers for Object Detection
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CVPR
2003
IEEE
14 years 9 months ago
Kullback-Leibler Boosting
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
Ce Liu, Heung-Yeung Shum
ANNPR
2006
Springer
13 years 11 months ago
Visual Classification of Images by Learning Geometric Appearances Through Boosting
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...
MMB
2012
Springer
259views Communications» more  MMB 2012»
12 years 3 months ago
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
Abstract. During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with h...
Ralf Jahr, Horia Calborean, Lucian Vintan, Theo Un...
CVPR
2001
IEEE
14 years 9 months ago
Learning Representative Local Features for Face Detection
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...
ICMCS
2006
IEEE
153views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Learning-Based Interactive Video Retrieval System
This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is pa...
Chi-Jiunn Wu, Hui-Chi Zeng, Szu-Hao Huang, Shang-H...