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» Learning to rank for content-based image retrieval
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AMR
2006
Springer
96views Multimedia» more  AMR 2006»
13 years 11 months ago
Learning to Retrieve Images from Text Queries with a Discriminative Model
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...
David Grangier, Florent Monay, Samy Bengio
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
13 years 12 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
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...
Qi Tian, Ying Wu, Thomas S. Huang
ECIR
2011
Springer
12 years 11 months ago
Dynamic Two-Stage Image Retrieval from Large Multimodal Databases
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...
Avi Arampatzis, Konstantinos Zagoris, Savvas A. Ch...
TKDE
2008
195views more  TKDE 2008»
13 years 7 months ago
Learning a Maximum Margin Subspace for Image Retrieval
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...
Xiaofei He, Deng Cai, Jiawei Han
CVPR
2010
IEEE
14 years 1 months ago
Image Retrieval via Probabilistic Hypergraph Ranking
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...
Yuchi Huang, Qingshan Liu, Shaoting Zhang, Metaxas...