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» Main subject detection via adaptive feature selection
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ICIP
2009
IEEE
13 years 2 months ago
Main subject detection via adaptive feature selection
In this paper we present an algorithm which uses adaptive selection of low-level features for main subject detection. The algorithm first computes low-level features such as contr...
Cuong T. Vu, Damon M. Chandler
ICIP
2009
IEEE
13 years 2 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
ICASSP
2010
IEEE
13 years 3 months ago
Human detection in images via L1-norm Minimization Learning
In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
Ran Xu, Baochang Zhang, Qixiang Ye, Jianbin Jiao
WOSS
2004
ACM
13 years 10 months ago
Resource-based approach to feature interaction in adaptive software
This paper proposes the RAFTING approach (Resourcebased Approach to FeaTure InteractioN) to address the feature interaction problem in the context of dynamically adapted software....
Jesus Bisbal, Betty H. C. Cheng
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
14 years 5 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...