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COMAD
2009
15 years 1 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...
118
Voted
CLEF
2009
Springer
14 years 10 months ago
The University of Amsterdam's Concept Detection System at ImageCLEF 2009
Our group within the University of Amsterdam participated in the large-scale visual concept detection task of ImageCLEF 2009. Our experiments focus on increasing the robustness of...
Koen E. A. van de Sande, Theo Gevers, Arnold W. M....
129
Voted
CVPR
2007
IEEE
16 years 2 months ago
Kernel Sharing With Joint Boosting For Multi-Class Concept Detection
Object/scene detection by discriminative kernel-based classification has gained great interest due to its promising performance and flexibility. In this paper, unlike traditional ...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
114
Voted
MM
2009
ACM
277views Multimedia» more  MM 2009»
15 years 7 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
137
Voted
CLEF
2009
Springer
14 years 10 months ago
Overview of the CLEF 2009 Large-Scale Visual Concept Detection and Annotation Task
The large-scale visual concept detection and annotation task (LS-VCDT) in ImageCLEF 2009 aims at the detection of 53 concepts in consumer photos. These concepts are structured in ...
Stefanie Nowak, Peter Dunker