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» Accuracy of distance metric learning algorithms
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98
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ICCV
2009
IEEE
14 years 8 months ago
A robust boosting tracker with minimum error bound in a co-training framework
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
Rong Liu, Jian Cheng, Hanqing Lu
114
Voted
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
14 years 5 months ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
167
Voted
GIS
2009
ACM
15 years 11 months ago
Sea Floor Bathymetry Trackline Surface Fitting Without Visible Artifacts Using ODETLAP
High quality, artifact-free fitting a bathymetry (sea-floor) surface to very unevenly spaced depth data from ship tracklines is possible with ODETLAP (Overdetermined Laplacian Par...
Tsz-Yam Lau, W. Randolph Franklin, You Li, Zhongyi...
81
Voted
ACCV
2009
Springer
15 years 4 months ago
Image-Set Based Face Recognition Using Boosted Global and Local Principal Angles
Face recognition using image-set or video sequence as input tends to be more robust since image-set or video sequence provides much more information than single snapshot about the ...
Xi Li, Kazuhiro Fukui, Nanning Zheng
100
Voted
APIN
1998
132views more  APIN 1998»
14 years 10 months ago
Evolution-Based Methods for Selecting Point Data for Object Localization: Applications to Computer-Assisted Surgery
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Shumeet Baluja, David Simon