TY - GEN
T1 - A multiple instance learning approach for content based image retrieval using one-class support vector machine
AU - Zhang, Chengcui
AU - Chen, Xin
AU - Chen, Min
AU - Chen, Shu Ching
AU - Shyu, Mei Ling
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - 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 One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm has been shown through comparative studies.
AB - 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 One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm has been shown through comparative studies.
UR - http://www.scopus.com/inward/record.url?scp=33750547285&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750547285&partnerID=8YFLogxK
U2 - 10.1109/ICME.2005.1521628
DO - 10.1109/ICME.2005.1521628
M3 - Conference contribution
AN - SCOPUS:33750547285
SN - 0780393325
SN - 9780780393325
T3 - IEEE International Conference on Multimedia and Expo, ICME 2005
SP - 1142
EP - 1145
BT - IEEE International Conference on Multimedia and Expo, ICME 2005
T2 - IEEE International Conference on Multimedia and Expo, ICME 2005
Y2 - 6 July 2005 through 8 July 2005
ER -