@inproceedings{2db013d8a75c450ca26bdad2ab070a28,
title = "Research on the selection of kernel function in SVM based facial expression recognition",
abstract = "Support vector machine(SVM) means that structural risk minimization principle is used to substitute Empirical risk minimization principle. SVM has shown the excellent performance in pattern recognition. The kernel function is the core of SVM, with which SVM can help to resolve many kinds of non-linear classification problems. Different kernel models and parameters have different result in the performance of the facial expression recognition system. The authors analyze the capability of polynomial kernel function and RBF kernel function in the facial expression recognition using the JAFFE expressions library. The work is valuable in the choise of kernel and its parameters in practice.",
keywords = "Facial expression recognition, RBF kernal function, Support vector machine, polynomial kernel function",
author = "Fuguang Wang and Ketai He and Ying Liu and Li Li and Xiaoguang Hu",
year = "2013",
doi = "10.1109/ICIEA.2013.6566586",
language = "英语",
isbn = "9781467363211",
series = "Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013",
pages = "1404--1408",
booktitle = "Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013",
note = "2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013 ; Conference date: 19-06-2013 Through 21-06-2013",
}