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» Evaluation strategies for image understanding and retrieval
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ICPR
2008
IEEE
14 years 8 months ago
Using an artificial imagination for texture retrieval
Our goal is to determine if artificially imagined or synthesized images can be beneficial to interactive visual search. We present a novel approach for using artificially imagined...
Bart Thomee, Mark J. Huiskes, Erwin M. Bakker, Mic...
CIVR
2004
Springer
194views Image Analysis» more  CIVR 2004»
14 years 25 days ago
A Test-Bed for Region-Based Image Retrieval Using Multiple Segmentation Algorithms and the MPEG-7 eXperimentation Model: The Sch
The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a referenc...
Vasileios Mezaris, Haralambos Doulaverakis, Raul M...
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
13 years 5 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
CIVR
2004
Springer
131views Image Analysis» more  CIVR 2004»
14 years 25 days ago
An Empirical Investigation of the Scalability of a Multiple Viewpoint CBIR System
Our work in content-based image retrieval (CBIR) relies on content-analysis of multiple representations of an image which we term multiple viewpoints or channels. The conceptual id...
James C. French, Xiangyu Jin, Worthy N. Martin
MIR
2006
ACM
229views Multimedia» more  MIR 2006»
14 years 1 months ago
Benchmarking image and video retrieval: an overview
Multimedia Information Retrieval (IR) techniques and associated systems are now numerous and justify the development of strategies and actions to objectively evaluate their capabi...
Stéphane Marchand-Maillet, Marcel Worring