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» An active feedback framework for image retrieval
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PRIS
2001
13 years 8 months ago
Relevance Feedback in Content-based Image Search
: Content-based image retrieval (CBIR) is a research area dedicated to address the retrieve and search multimedia documents for digital libraries. Relevance feedback is a powerful ...
HongJiang Zhang
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
14 years 1 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose
BDA
2007
13 years 8 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
CVPR
2006
IEEE
14 years 9 months ago
A Simple Bayesian Framework for Content-Based Image Retrieval
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
Katherine A. Heller, Zoubin Ghahramani
CIVR
2008
Springer
173views Image Analysis» more  CIVR 2008»
13 years 9 months ago
Adaptive multiple feedback strategies for interactive video search
In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. We first segregate interactive feedback into 3 distinct types (recall-driven relev...
Huan-Bo Luan, Yantao Zheng, Shi-Yong Neo, Yongdong...