Contractive Autoencoder and SVM for Recognition of Handwritten Devanagari Numerals

被引：0
|
作者：
Kabra, Ruhi R. [1 ]
机构：
[1] MSSs Coll Engn & Technol, Dept Comp Sci & Engn, Jalna, India
来源：
2017 1ST INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND INFORMATION MANAGEMENT (ICISIM) | 2017年
关键词：
Contractive autoencoder; SVM; Handwritten numerals recognition;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Representation of data is very important in case of machine learning. Better the representation, the classifiers will give better results. Contractive autoencoders are used to learn the representation of data which are robust to small changes in the input. This paper uses contractive autoencoder and SVM classifier for handwritten Devanagari numerals recognition. The accuracy obtained using CAE+SVM is 96 %.
引用
收藏
页码：26 / 29
页数：4
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