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» Estimating Missing Features to Improve Multimedia Retrieval
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ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
15 years 4 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
MM
2006
ACM
142views Multimedia» more  MM 2006»
15 years 5 months ago
Large-scale video retrieval via semantic classification
ons for this project. Most recent ones are listed at the end of this abstract. In the future, feature selection will be integrated in the multi-class EM algorithm to improve the pe...
Hangzai Luo, Jianping Fan
MTA
2006
140views more  MTA 2006»
14 years 11 months ago
Audio indexing: primary components retrieval
This work addresses the soundtrack indexing of multimedia documents. We present and merge two audio classification tools that we have developed. The first one, a speech music clas...
Julien Pinquier, Régine André-Obrech...
ECIR
2009
Springer
15 years 9 months ago
Regression Rank: Learning to Meet the Opportunity of Descriptive Queries
Abstract. We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically, knowledge of effective term weights on ...
Matthew Lease, James Allan, W. Bruce Croft
CIVR
2008
Springer
245views Image Analysis» more  CIVR 2008»
15 years 1 months ago
Probabilistic optimized ranking for multimedia semantic concept detection via RVM
We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize ...
Yantao Zheng, Shi-Yong Neo, Tat-Seng Chua, Qi Tian