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» MOSAIC: A fast multi-feature image retrieval system
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COOPIS
2004
IEEE
13 years 11 months ago
Ontology for Nature-Scene Image Retrieval
This paper presents a framework for building an ontology to provide semantic interpretations in image contents. The novelty of this framework comes from building a MPEG-7 ontology ...
Song Liu, Liang-Tien Chia, Syin Chan
IJCAI
2007
13 years 9 months ago
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...
MM
2006
ACM
124views Multimedia» more  MM 2006»
14 years 1 months ago
Blazingly fast image copyright enforcement
Many photo agencies use the web to sell access to their image collections. Despite significant security measures, images may be stolen and distributed, making it necessary to det...
Herwig Lejsek, Friðrik Heiðar Ásmun...
SIBGRAPI
2003
IEEE
14 years 22 days ago
Using Efficient Visual Exploration Techniques to Evaluate Features for Content-Based Image Retrieval
This paper presents a novel visual approach to evaluate, in a fast and effective way, the development of new image feature extraction techniques concerning content-based image ret...
José Fernando Rodrigues Jr., César A...
MTA
2010
175views more  MTA 2010»
13 years 5 months ago
Building a web-scale image similarity search system
As the number of digital images is growing fast and Content-based Image Retrieval (CBIR) is gaining in popularity, CBIR systems should leap towards Webscale datasets. In this paper...
Michal Batko, Fabrizio Falchi, Claudio Lucchese, D...