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CISST
2004
164views Hardware» more  CISST 2004»
13 years 9 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
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 ...
CIVR
2005
Springer
156views Image Analysis» more  CIVR 2005»
14 years 1 months ago
Content-Based Object Movie Retrieval by Use of Relevance Feedback
Abstract. Object movie refers to a set of images captured from different perspectives around a 3D object. Object movie is a good representation of a physical object because it can ...
Li-Wei Chan, Cheng-Chieh Chiang, Yi-Ping Hung
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...
ACIVS
2005
Springer
14 years 1 months ago
Interactive Object-Based Retrieval Using Relevance Feedback
In this paper we present an interactive, object-based video retrieval system which features a novel query formulation method that is used to iteratively refine an underlying model...
Sorin Sav, Hyowon Lee, Noel E. O'Connor, Alan F. S...