96 search results - page 7 / 20 » Learning to rank for content-based image retrieval |
AMR
2006
Springer
15 years 1 months ago
2006
Springer
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval pe...
ICMCS
2000
IEEE
15 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...
112
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ECIR
2011
Springer
14 years 1 months ago
2011
Springer
Abstract. Content-based image retrieval (CBIR) with global features is notoriously noisy, especially for image queries with low percentages of relevant images in a collection. More...
104
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TKDE
2008
14 years 9 months ago
2008
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
CVPR
2010
IEEE
15 years 3 months ago
2010
IEEE
In this paper, we propose a new transductive learning framework for image retrieval, in which images are taken as vertices in a weighted hypergraph and the task of image search is...