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» Relevance Feedback in Content-based Image Search
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MTA
2002
166views more  MTA 2002»
13 years 4 months ago
MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback
ThefieldofContent-BasedVisualInformationRetrieval(CBVIR)hasexperiencedtremendousgrowth in the recent years and many research groups are currently working on solutions to the proble...
Oge Marques, Borko Furht
VISUAL
1999
Springer
13 years 9 months ago
Relevance Feedback and Term Weighting Schemes for Content-Based Image Retrieval
This paper describes the application of techniques derived from text retrieval research to the content-based querying of image databases. Speci cally, the use of inverted les, fre...
David Squire, Wolfgang Müller 0002, Henning M...
EDBT
2006
ACM
172views Database» more  EDBT 2006»
14 years 5 months ago
Fast Query Point Movement Techniques with Relevance Feedback for Content-Based Image Retrieval
Abstract. Target search in content-based image retrieval (CBIR) systems refers to finding a specific (target) image such as a particular registered logo or a specific historical ph...
Danzhou Liu, Kien A. Hua, Khanh Vu, Ning Yu
RIAO
2000
13 years 6 months ago
Image indexation and content based search using pre-attentive similarities
We introduce in this paper the general architecture of an image search engine based on pre-attentive similarities. The components of this system are presented and some of them are...
Alexander Heinrichs, Dimitri Koubaroulis, Barbara ...
ICTIR
2009
Springer
13 years 11 months ago
A Four-Factor User Interaction Model for Content-Based Image Retrieval
In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques i...
Haiming Liu 0002, Victoria S. Uren, Dawei Song, St...