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» Diversifying the image retrieval results
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74
Voted
CIVR
2004
Springer
111views Image Analysis» more  CIVR 2004»
15 years 3 months ago
An Inference Network Approach to Image Retrieval
Most image retrieval systems only allow a fragment of text or an example image as a query. Most users have more complex information needs that are not easily expressed in either of...
Donald Metzler, R. Manmatha
MMM
2005
Springer
202views Multimedia» more  MMM 2005»
15 years 3 months ago
Image Mining and Retrieval Using Hierarchical Support Vector Machines
For some time now, image retrieval approaches have been developed that use low-level features, such as colour histograms, edge distributions and texture measures. What has been la...
Ross Brown, Binh Pham
CVPR
2005
IEEE
15 years 11 months ago
Evaluating Image Retrieval
We present a comprehensive strategy for evaluating image retrieval algorithms. Because automated image retrieval is only meaningful in its service to people, performance character...
Nikhil V. Shirahatti, Kobus Barnard
83
Voted
NIPS
2004
14 years 11 months ago
Instance-Based Relevance Feedback for Image Retrieval
High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of t...
Giorgio Giacinto, Fabio Roli
98
Voted
AINA
2007
IEEE
15 years 4 months ago
Mining Visual Knowledge for Multi-Lingual Image Retrieval
Users commonly rely just on scarce textual annotation when their searches for images are semantic or conceptual based. Rich visual information is often thrown away in basic annota...
Masashi Inoue