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» Relevance Feedback in Content-based Image Search
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MTA
2002
166views more  MTA 2002»
13 years 5 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 10 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 6 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 7 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
14 years 12 days 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...