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ECIR
2010
Springer
13 years 10 months ago
Query Difficulty Prediction for Contextual Image Retrieval
Abstract. This paper explores how to predict query difficulty for contextual image retrieval. We reformulate the problem as the task of predicting how difficult to represent a quer...
Xing Xing, Yi Zhang 0001, Mei Han
ICIP
2000
IEEE
14 years 10 months ago
A Hierarchical Characterization Scheme for Image Retrieval
* In this paper, we present a study of hierarchically characterizing image content from coarse level to fine level conducted using a series of shape features as a case in point. I...
Liu Wenyin, Tao Wang, HongJiang Zhang
SSIAI
2000
IEEE
14 years 1 months ago
Content Based Retrieval for Remotely Sensed Imagery
We present a framework for content based retrieval (CBR) of remotely sensed imagery. The main focus of our research is the segmentation step in CBR. A bank of gabor filters is use...
Badrinarayan Raghunathan, Scott T. Acton
TIP
2008
185views more  TIP 2008»
13 years 8 months ago
Active Learning Methods for Interactive Image Retrieval
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
Philippe Henri Gosselin, Matthieu Cord
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
13 years 7 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...