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» On Combining Classifiers
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ICCV
2005
IEEE
16 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICPR
2006
IEEE
16 years 7 months ago
A Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions
This paper proposes a new generic object recognition system based on multi-scale affineinvariant image regions. Image segments are obtained by a watershed transform of the princip...
Wei Zhang, Hongli Deng, Thomas G. Dietterich, Eric...
CVPR
2010
IEEE
15 years 10 months ago
Multi-Cue Pedestrian Classification with Partial Occlusion Handling
This paper presents a novel mixture-of-experts framework for pedestrian classification with partial occlusion handling. The framework involves a set of component-based expert clas...
Markus Enzweiler, Angela Eigenstetter, Bernt Schie...
SIGIR
2003
ACM
15 years 11 months ago
Image classification using hybrid neural networks
Use of semantic content is one of the major issues which needs to be addressed for improving image retrieval effectiveness. We present a new approach to classify images based on t...
Chih-Fong Tsai, Kenneth McGarry, John Tait
ICMLA
2004
15 years 7 months ago
LASSO: a learning architecture for semantic web ontologies
Expressing web page content in a way that computers can understand is the key to a semantic web. Generating ontological information from the web automatically using machine learni...
Christopher N. Hammack, Stephen D. Scott