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» A two-level relevance feedback mechanism for image retrieval
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MM
2005
ACM
171views Multimedia» more  MM 2005»
15 years 3 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
MM
2003
ACM
116views Multimedia» more  MM 2003»
15 years 3 months ago
Negative pseudo-relevance feedback in content-based video retrieval
Video information retrieval requires a system to find information relevant to a query which may be represented simultaneously in different ways through a text description, audio...
Rong Yan, Alexander G. Hauptmann, Rong Jin
CVPR
2001
IEEE
15 years 11 months ago
Adaptive Quasiconformal Kernel Metric for Image Retrieval
This paper presents a new approach to ranking relevant images for retrieval. Distance in the feature space associated with a kernel is used to rank relevant images. An adaptive qu...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
CIVR
2006
Springer
141views Image Analysis» more  CIVR 2006»
15 years 1 months ago
Context-Aware Media Retrieval
In this paper we propose a representation framework for dynamic multi-sensory knowledge and user context, and its application in media retrieval. We provide a definition of context...
Ankur Mani, Hari Sundaram
CVPR
2004
IEEE
15 years 1 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp