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MIR
2004
ACM
171views Multimedia» more  MIR 2004»
13 years 10 months ago
Mean version space: a new active learning method for content-based image retrieval
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
Jingrui He, Hanghang Tong, Mingjing Li, HongJiang ...
PR
2011
12 years 7 months ago
Content-based image retrieval with relevance feedback using random walks
In this paper we propose a novel approach to content-based image retrieval with relevance feedback, which is based on the random walker algorithm introduced in the context of inte...
Samuel Rota Bulò, Massimo Rabbi, Marcello P...
ICIAR
2007
Springer
13 years 11 months ago
Image Retrieval Using Transaction-Based and SVM-Based Learning in Relevance Feedback Sessions
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...
Xiaojun Qi, Ran Chang
PR
2007
205views more  PR 2007»
13 years 4 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
VDB
1998
117views Database» more  VDB 1998»
13 years 6 months ago
Textural Features and Relevance Feedback for Image Retrieval
This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentati...
Eugenio Di Sciascio, Giacomo Piscitelli, Augusto C...