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» An active feedback framework for image retrieval
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SPIESR
1998
195views Database» more  SPIESR 1998»
13 years 8 months ago
Relevance Feedback Techniques in Interactive Content-Based Image Retrieval
Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many system...
Yong Rui, Thomas S. Huang, Sharad Mehrotra
ICASSP
2007
IEEE
14 years 1 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
PR
2007
205views more  PR 2007»
13 years 6 months ago
Active learning for image retrieval with Co-SVM
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we proposed an active learning alg...
Jian Cheng, Kongqiao Wang
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
ICMCS
2005
IEEE
184views Multimedia» more  ICMCS 2005»
14 years 29 days ago
Fuzzy relevance feedback in content-based image retrieval systems using radial basis function network
This paper presents a new framework called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems based on soft-decision. An efficient learning appro...
Kim-Hui Yap, Kui Wu