New support vector-based design method for binary hierarchical classifiers for multi-class classification problems

DOI10.1016/J.NEUNET.2007.12.005zbMath1254.68241DBLPjournals/nn/WangC08OpenAlexW2041971019WikidataQ47982675 ScholiaQ47982675MaRDI QIDQ1932013

Yu-Chiang Frank Wang, David Casasent

Publication date: 17 January 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2007.12.005

zbMATH Keywords

pattern recognitionautomatic target recognitionsupport vector machinehierarchical classifier

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (1)

A novel framework for multi-class classification via ternary smooth support vector machine

Cites Work

• Unnamed Item
• Hierarchical fusion of multiple classifiers for hyperspectral data analysis

This page was built for publication: New support vector-based design method for binary hierarchical classifiers for multi-class classification problems