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» MILIS: Multiple Instance Learning with Instance Selection
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ICIP
2005
IEEE
14 years 9 months ago
A complementary SVMs-based image annotation system
A novel automatic image annotation system is proposed, which integrates two sets of SVMs (Support Vector Machines), namely the MIL-based (Multiple Instance Learning) and global-fe...
Yutao Han, Xiaojun Qi
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 months ago
Active Learning from Multiple Noisy Labelers with Varied Costs
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Yaling Zheng, Stephen D. Scott, Kun Deng
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 2 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
ACCV
2009
Springer
14 years 2 months ago
Human Action Recognition Using HDP by Integrating Motion and Location Information
The method based on local features has an advantage that the important local motion feature is represented as bag-of-features, but lacks the location information. Additionally, in ...
Yasuo Ariki, Takuya Tonaru, Tetsuya Takiguchi
ISMIR
2004
Springer
126views Music» more  ISMIR 2004»
14 years 1 months ago
Dance music classification: A tempo-based approach
Recent research has studied the relevance of various features for automatic genre classification, showing the particular importance of tempo in dance music classification. We co...
Fabien Gouyon, Simon Dixon