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» Instance-Based Relevance Feedback for Image Retrieval
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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...
PR
2007
205views more  PR 2007»
13 years 7 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
ICMCS
2006
IEEE
155views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Region-Based Image Retrieval using Radial Basis Function Network
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified u...
Kui Wu, Kim-Hui Yap, Lap-Pui Chau
ECIR
2006
Springer
13 years 9 months ago
Can a Workspace Help to Overcome the Query Formulation Problem in Image Retrieval?
We have proposed a novel image retrieval system that incorporates a workspace where users can organise their search results. A task-oriented and usercentred experiment has been dev...
Jana Urban, Joemon M. Jose
ICIP
2003
IEEE
14 years 9 months ago
An ontology approach to object-based image retrieval
In this paper, an image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segme...
Vasileios Mezaris, Ioannis Kompatsiaris, Michael G...