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ICIP
2000
IEEE
14 years 9 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
KES
2004
Springer
14 years 29 days ago
Content-Based Image Retrieval Using Multiple Representations
Many different approaches for content-based image retrieval have been proposed in the literature. Successful approaches consider not only simple features like color, but also take ...
Karin Kailing, Hans-Peter Kriegel, Stefan Schö...
SSPR
1998
Springer
13 years 11 months ago
Semantic Content Based Image Retrieval Using Object-Process Diagrams
Abstract. The increase in accessability to on-line visual data has promoted the interest in browsing and retrieval of images from Image Databases. Current approaches assume either ...
Dov Dori, Hagit Zabrodsky Hel-Or
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
14 years 7 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung