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ECML
2004
Springer
13 years 11 months ago
Exploiting Unlabeled Data in Content-Based Image Retrieval
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang
AAAI
2007
13 years 8 months ago
Semi-Supervised Learning with Very Few Labeled Training Examples
In semi-supervised learning, a number of labeled examples are usually required for training an initial weakly useful predictor which is in turn used for exploiting the unlabeled e...
Zhi-Hua Zhou, De-Chuan Zhan, Qiang Yang
PAMI
2010
225views more  PAMI 2010»
13 years 1 months ago
Semi-Supervised Classification via Local Spline Regression
Abstract--This paper presents local spline regression for semisupervised classification. The core idea in our approach is to introduce splines developed in Sobolev space to map the...
Shiming Xiang, Feiping Nie, Changshui Zhang
TIP
2008
185views more  TIP 2008»
13 years 5 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
ICIP
2009
IEEE
13 years 4 months ago
Optimization on active learning strategy for object category retrieval
Active learning is a framework that has attracted a lot of research interest in the content-based image retrieval (CBIR) in recent years. To be effective, an active learning syste...
David Gorisse, Matthieu Cord, Frédér...