Result: The study of character recognition based on fuzzy support vector machine
Title:
The study of character recognition based on fuzzy support vector machine
Authors:
Source:
Intelligent computing in signal processing and pattern recognition (International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006)0ICIC 2006. :1087-1092
Publisher Information:
Berlin: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 6 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Documentation, Computer science, Informatique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Algorithme flou, Fuzzy algorithm, Algoritmo borroso, Analyse statistique, Statistical analysis, Análisis estadístico, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Logique floue, Fuzzy logic, Lógica difusa, Machine exemple support, Vector support machine, Máquina ejemplo soporte, Méthode noyau, Kernel method, Método núcleo, Reconnaissance caractère, Character recognition, Reconocimiento carácter, Reconnaissance forme, Pattern recognition, Reconocimiento patrón, Traitement image, Image processing, Procesamiento imagen
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
College of Computer Science and Information Engineering, TUST. Tianjin University of Science and Technology, Tianjin, China
ISSN:
0170-8643
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.18315957
Database:
PASCAL Archive
Further Information
Support vector machine (SVM) and v-SVM are novel type of learning machine, which have shown to provide better generalization performance than traditional techniques. This thesis introduces a new type of fuzzy support vector machine (Fv-SVM), which based on v-SVM. The new algorithm considers that the input samples have different contributions to the final result, so fuzzy memberships are used to determine the effects of input samples. It also discusses in detail the core algorithms determine the fuzzy memberships based on kernel methods. In the experiments Fv-SVM is used for character recognition. The results show that Fv-SVM has low error rate and better generalization ability.