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» A Support Vector Clustering Method
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TMM
2010
270views Management» more  TMM 2010»
14 years 9 months ago
Sequence Multi-Labeling: A Unified Video Annotation Scheme With Spatial and Temporal Context
Abstract--Automatic video annotation is a challenging yet important problem for content-based video indexing and retrieval. In most existing works, annotation is formulated as a mu...
Yuanning Li, YongHong Tian, Ling-Yu Duan, Jingjing...
ICPR
2008
IEEE
16 years 3 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
125
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VISUALIZATION
2005
IEEE
15 years 8 months ago
Illuminated Lines Revisited
For the rendering of vector and tensor fields, several texturebased volumetric rendering methods were presented in recent years. While they have indisputable merits, the classica...
Ovidio Mallo, Ronald Peikert, Christian Sigg, Fili...
138
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BIBE
2001
IEEE
15 years 6 months ago
Gene Classification using Expression Profiles: A Feasibility Study
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomi...
Michihiro Kuramochi, George Karypis
146
Voted
NIPS
2003
15 years 4 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller