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» Relevance Feedback in Content-based Image Search
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MM
2004
ACM
152views Multimedia» more  MM 2004»
14 years 1 months ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...
CVPR
2007
IEEE
13 years 11 months ago
Diverse Active Ranking for Multimedia Search
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
MM
2004
ACM
173views Multimedia» more  MM 2004»
14 years 1 months ago
Cortina: a system for large-scale, content-based web image retrieval
Recent advances in processing and networking capabilities of computers have led to an accumulation of immense amounts of multimedia data such as images. One of the largest reposit...
Till Quack, Ullrich Mönich, Lars Thiele, B. S...
SAMT
2007
Springer
203views Multimedia» more  SAMT 2007»
14 years 1 months ago
A Generic Framework for Semantic Medical Image Retrieval
Performing simple keyword-based search has long been the only way to access information. But for a truly comprehensive search on multimedia data, this approach is no longer sucien...
Manuel Möller, Michael Sintek
MIR
2004
ACM
171views Multimedia» more  MIR 2004»
14 years 1 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 ...