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» Content-Based Color Image Retrieval with Relevance Feedback
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JDCTA
2010
170views more  JDCTA 2010»
13 years 3 months ago
Color and Texture Feature For Content Based Image Retrieval
Content based image retrieval (CBIR) has been one of the most important research areas in computer science for the last decade. A retrieval method which combines color and texture...
Jianhua Wu, Zhaorong Wei, Youli Chang
ICPR
2000
IEEE
14 years 9 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
ICIP
2008
IEEE
14 years 10 months ago
Long term learning for image retrieval over networks
In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...
David Picard, Arnaud Revel, Matthieu Cord
BMVC
2001
13 years 11 months ago
Salient Points for Content-Based Retrieval
In image retrieval, global features related to color or texture are commonly used to describe the image content. The use of interest points in contentbased image retrieval allows ...
Nicu Sebe, Michael S. Lew
MTA
2000
165views more  MTA 2000»
13 years 8 months ago
Approximating Content-Based Object-Level Image Retrieval
Object-level image retrieval is an active area of research. Given an image, a human observerdoesnot see randomdots of colors. Rather,he she observesfamiliarobjectsin the image. The...
Wynne Hsu, Tat-Seng Chua, Hung Keng Pung