110 search results - page 5 / 22 » Stretching Bayesian Learning in the Relevance Feedback of Im... |
ICMCS
2000
IEEE
14 years 1 months ago
2000
IEEE
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
ICIP
2003
IEEE
14 years 10 months ago
2003
IEEE
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
ICCV
2007
IEEE
14 years 11 months ago
2007
IEEE
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
ICMCS
2007
IEEE
14 years 3 months ago
2007
IEEE
This paper introduces a flexible learning approach for image retrieval with relevance feedback. A semantic repository is constructed offline by applying the k-nearest-neighborbase...
CIKM
2008
Springer
13 years 11 months ago
2008
Springer
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...