SVM-based active feedback in image retrieval using clustering and unlabeled data

DOI10.1016/j.patcog.2008.01.023zbMath1151.68397OpenAlexW2125782835MaRDI QIDQ931698

Daiki Masumoto, Yuehong Wang, Shigemi Nagata, Takayuki Baba, Rujie Liu

Publication date: 26 June 2008

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2008.01.023

zbMATH Keywords

clusteringimage retrievalSVMunlabeled datarelevance feedback

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Pattern recognition, speech recognition (68T10) Information storage and retrieval of data (68P20)

Related Items (7)

CTSVM: a robust twin support vector machine with correntropy-induced loss function for binary classification problems ⋮ Least squares twin multi-class classification support vector machine ⋮ Quantum speedup for pool-based active learning ⋮ Using robust dispersion estimation in support vector machines ⋮ Linear Classification of Data with Support Vector Machines and Generalized Support Vector Machines ⋮ Linear and Nonlinear Classifiers of Data with Support Vector Machines and Generalized Support Vector Machines ⋮ A new and informative active learning approach for support vector machine

Uses Software

• PicHunter

Cites Work

• Semi-supervised learning on Riemannian manifolds
• Constructing support vector machine ensemble.
• Bayesian relevance feedback for content-based image retrieval

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