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Erschienen in:
An Image Steganalysis Algorithm Based on Rotation Forest Transformation and Multiple Classifiers Ensemble Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Target Recognition Method Based on Multi-class SVM and Evidence Theory

verfasst von : Wen Quan, Jian Wang, Lei Lei, Maolin Gao

Erschienen in: Advances in Internetworking, Data & Web Technologies

Verlag: Springer International Publishing

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Abstract

In order to conquer the hard outputs defect of Support Vector Machine (SVM) and extend its application, an improved target recognition method based on Multi-class Support Vector Machine (MSVM) is proposed. Firstly, the typical Probability Modeling methodologies of MSVM were deeply analyzed. Secondly, the structure of one-against-one multi-class method which matches with Basic Probability Assignment (BPA) outputs of evidence theory by coincide, so a special Multi-class BPA output method is derived, and multi-sensor target recognition model based on MSVM and two-layer evidence theory is constructed. Finally, the results of experiments show that the proposed approach can not only conquer the overlap area of one-against-one multi-class method, but also improve classification accuracy.

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Metadaten
Titel
Target Recognition Method Based on Multi-class SVM and Evidence Theory
verfasst von
Wen Quan
Jian Wang
Lei Lei
Maolin Gao
Copyright-Jahr
2018
Buch
Advances in Internetworking, Data & Web Technologies

Print ISBN: 978-3-319-59462-0

Electronic ISBN: 978-3-319-59463-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-59463-7_26