DocumentCode
596566
Title
BP alogrithm in pattern recognition of glass defects
Author
Shufang Li
Author_Institution
Dept. of Inf. Eng., Environ. Manage. Coll. of China, Qinhuangdao, China
fYear
2012
fDate
18-20 Oct. 2012
Firstpage
183
Lastpage
187
Abstract
According to the characteristics of glass defects, through analyzing the advantages and disadvantages of the traditional BP algorithm, an improved BP neural network recognition algorithm is applied to the glass defect classification and character recognition. Experimental results show that compared with traditional BP recognition algorithm, convergence speed of the algorithm is fast and the identification of false positives is low.
Keywords
automatic optical inspection; backpropagation; character recognition; convergence; glass; image classification; neural nets; production engineering computing; character recognition; convergence speed; false positive identification; glass defect classification; improved BP neural network recognition algorithm; pattern recognition; Algorithm design and analysis; Approximation algorithms; Classification algorithms; Glass; Neurons; Tin; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-1743-6
Type
conf
DOI
10.1109/ICACI.2012.6463147
Filename
6463147
Link To Document