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CVPR
2007
IEEE
14 years 2 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
CVPR
2007
IEEE
15 years 3 days ago
Composite Models of Objects and Scenes for Category Recognition
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
David J. Crandall, Daniel P. Huttenlocher
ICPR
2006
IEEE
14 years 11 months ago
Ent-Boost: Boosting Using Entropy Measure for Robust Object Detection
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...
Duy-Dinh Le, Shin'ichi Satoh
ICML
2007
IEEE
14 years 11 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
COLT
1997
Springer
14 years 2 months ago
General Convergence Results for Linear Discriminant Updates
The problem of learning linear discriminant concepts can be solved by various mistake-driven update procedures, including the Winnow family of algorithms and the well-known Percep...
Adam J. Grove, Nick Littlestone, Dale Schuurmans