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CVPR
2006
IEEE
14 years 7 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
ICCV
2005
IEEE
14 years 6 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
DAC
2008
ACM
14 years 5 months ago
Scan chain clustering for test power reduction
An effective technique to save power during scan based test is to switch off unused scan chains. The results obtained with this method strongly depend on the mapping of scan flip-...
Christian G. Zoellin, Hans-Joachim Wunderlich, Jen...
PAMI
2006
128views more  PAMI 2006»
13 years 4 months ago
On Weighting Clustering
Recent papers and patents in iterative unsupervised learning have emphasized a new trend in clustering. It basically consists of penalizing solutions via weights on the instance po...
Richard Nock, Frank Nielsen
14
Voted
ICASSP
2007
IEEE
13 years 11 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian