Enhancing Visual Concept Detection by a Novel Matrix Modular Scheme on SVM View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Zhong-Qiu Zhao , Hervé Glotin

ABSTRACT

A novel Matrix Modular Support Vector Machine(MMSVM) classifier is proposed to partition a visual concept problem into many easier two-class problems.This MMSVM shows significant detection improvements on the ImageClef2008 VCDT task, with a relative reduction of 15% of the classification error, compared with usual SVMs.

PAGES

640-643

Book

TITLE

Evaluating Systems for Multilingual and Multimodal Information Access

ISBN

978-3-642-04446-5
978-3-642-04447-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-04447-2_80

DOI

http://dx.doi.org/10.1007/978-3-642-04447-2_80

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017428085


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