DocumentCode
2344287
Title
Feature extraction and selection of neural network
Author
Chengdong, Wu ; Feng, Gao ; Shaohua, Ma
Author_Institution
Shenyang Archit. & Civil Eng. Inst., Shenyang, China
Volume
2
fYear
2000
fDate
2000
Firstpage
1103
Abstract
This paper presents the feature extraction and feature selection methods for the wood veneer inspection application using neural network classifiers. The paper emphatically describes the statistical method of feature extraction and feature selection. The intra-class variation, inter-class variation and feature correlation are introduced to measure the discriminatory power of the wood veneer image
Keywords
automatic optical inspection; correlation methods; feature extraction; neural nets; pattern classification; statistical analysis; wood processing; correlation method; feature extraction; feature selection; neural network; pattern classification; statistical method; wood veneer inspection; Feature extraction; Finite impulse response filter; Neural networks; Power measurement; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location
Hefei
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.863410
Filename
863410
Link To Document