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» Evaluating learning algorithms and classifiers
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CVPR
2012
IEEE
13 years 7 months ago
Contextual Boost for Pedestrian Detection
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In...
Yuanyuan Ding, Jing Xiao
ECCV
2008
Springer
16 years 6 months ago
A Pose-Invariant Descriptor for Human Detection and Segmentation
We present a learning-based, sliding window-style approach for the problem of detecting humans in still images. Instead of traditional concatenation-style image location-based feat...
Zhe Lin, Larry S. Davis
CIDM
2007
IEEE
15 years 11 months ago
Prediction of Abnormal Behaviors for Intelligent Video Surveillance Systems
–The OBSERVER is a video surveillance system that detects and predicts abnormal behaviors aiming at the intelligent surveillance concept. The system acquires color images from a ...
Duarte Duque, Henrique Santos, Paulo Cortez
CIKM
2008
Springer
15 years 6 months ago
Semi-supervised text categorization by active search
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
HIS
2008
15 years 6 months ago
Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules
Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...