Add to ORKGWe formulate the problem of retrieving images from visual databases as a problem of Bayesian inference. This leads to natural and effective solutions for two of the most challenging issues in the design of a retrieval system: providing support for region-based queries without requiring prior image segmentation, and accounting for user-feedback during a retrieval session. We present a new learning algorithm that relies on belief propagation to account for both positive and negative examples of the user’s interests.
The retrieval performance of content-based image retrieval (CBIR) systems is often disappointingly l...
Image retrieval using multiple features often uses explicit weights that represent the importance of...
We take the benefit of improvements in optical devices for multimedia data storage, jointly with dev...
multimedia databases MULLER, Wolfgang, et al. It has been widely recognised that the difference betw...
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although...
It has been widely recognised that the difference between the level of abstraction of the formulatio...
Despite the efforts to reduce the so-called semantic gap between the user’s perception of image simi...
Despite the efforts to reduce the so-called semantic gap between the user’s perception of image simi...
Hunting moving targets: an extension to Bayesian methods in multimedia databases MULLER, Wolfgang, e...
Despite the efforts to reduce the so-called semantic gap between the user's perception of image simi...
[[abstract]]This paper presents a generalized Bayesian framework for relevance feedback in content-b...
Content-free image retrieval uses accumulated user feedback records to retrieve images without analy...
A new algorithm and systematic evaluation is presented for searching a database via relevance feedba...
Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program ...
In this paper we address several aspects of the learning problem in content-based image retrieval (C...
The retrieval performance of content-based image retrieval (CBIR) systems is often disappointingly l...
Image retrieval using multiple features often uses explicit weights that represent the importance of...
We take the benefit of improvements in optical devices for multimedia data storage, jointly with dev...
multimedia databases MULLER, Wolfgang, et al. It has been widely recognised that the difference betw...
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although...
It has been widely recognised that the difference between the level of abstraction of the formulatio...
Despite the efforts to reduce the so-called semantic gap between the user’s perception of image simi...
Despite the efforts to reduce the so-called semantic gap between the user’s perception of image simi...
Hunting moving targets: an extension to Bayesian methods in multimedia databases MULLER, Wolfgang, e...
Despite the efforts to reduce the so-called semantic gap between the user's perception of image simi...
[[abstract]]This paper presents a generalized Bayesian framework for relevance feedback in content-b...
Content-free image retrieval uses accumulated user feedback records to retrieve images without analy...
A new algorithm and systematic evaluation is presented for searching a database via relevance feedba...
Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program ...
In this paper we address several aspects of the learning problem in content-based image retrieval (C...
The retrieval performance of content-based image retrieval (CBIR) systems is often disappointingly l...
Image retrieval using multiple features often uses explicit weights that represent the importance of...
We take the benefit of improvements in optical devices for multimedia data storage, jointly with dev...