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» Unifying Keywords and Visual Contents in Image Retrieval
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MM
2006
ACM
130views Multimedia» more  MM 2006»
15 years 3 months ago
An unsupervised method for clustering images based on their salient regions of interest
We have developed a biologically-motivated, unsupervised way of grouping together images whose salient regions of interest (ROIs) are perceptually similar regardless of the visual...
Gustavo B. Borba, Humberto R. Gamba, Oge Marques, ...
ICPR
2008
IEEE
15 years 4 months ago
Interactive feature visualization for image retrieval
Most systems for content based image retrieval (CBIR) employ low level image features as a similarity measure. The problem of CBIR systems is that they are a “black box” to th...
Johannes Imo, Sebastian Klenk, Gunther Heidemann
VISUAL
2005
Springer
15 years 3 months ago
Surveying the Reality of Semantic Image Retrieval
Abstract. An ongoing project is described which seeks to add to our understanding about the real challenge of semantic image retrieval. Consideration is given to the plurality of t...
Peter G. B. Enser, Christine J. Sandom, Paul H. Le...
MIR
2005
ACM
133views Multimedia» more  MIR 2005»
15 years 3 months ago
Probabilistic web image gathering
We propose a new method for automated large scale gathering of Web images relevant to specified concepts. Our main goal is to build a knowledge base associated with as many conce...
Keiji Yanai, Kobus Barnard
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
15 years 9 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung