DocumentCode
389272
Title
A learning strategy in CBIR system design
Author
Gong, Sheng-rong ; Wang, Zhao-hui ; Zhao, Jian-Min
Volume
2
fYear
2002
fDate
2002
Firstpage
754
Abstract
In this paper, a flexible relevance feedback learning strategy is proposed. Applying the learning strategy, the user can embed semantic information by interacting continuously with the retrieval system. Experimental results show that the designed learning strategy is robust, efficient and effective.
Keywords
content-based retrieval; image retrieval; learning (artificial intelligence); relevance feedback; CBIR system design; feature vector; flexible relevance feedback learning strategy; image retrieval; query vector; retrieval system; robust learning strategy; semantic information; Content based retrieval; Feedback; Image retrieval; Information retrieval; Internet; Petroleum; Prototypes; Query processing; Robustness; Shape measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN
0-7803-7508-4
Type
conf
DOI
10.1109/ICMLC.2002.1174480
Filename
1174480
Link To Document