Defects Detection of TFT Lines of Flat Panel Displays Using an Evolutionary Optimized Recurrent Neural Network

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ISSN Print: 2160-8830
ISSN Online: 2160-8849
www.scirp.org/journal/ajor
E-mail: ajor@scirp.org

"Defects Detection of TFT Lines of Flat Panel Displays Using an Evolutionary Optimized Recurrent Neural Network"
written by Hapu Arachchilage Abeysundara, Hiroshi Hamori, Takeshi Matsui, Masatoshi Sakawa,
published by American Journal of Operations Research, Vol.4 No.3, 2014

has been cited by the following article(s):

[1]	A Review on Recent Advances in Vision-based Defect Recognition towards Industrial Intelligence
	2021

[2]	Machine Learning-based Methods for Detecting Defects in Glass Substrate from Non-contact Electrical Sensor Data
	2018

[3]	DEFECTS INSPECTION PROCESS OF FLAT PANEL DISPLAY FABRICATION THROUGH NEURAL NETWORKS
	Thesis, 2015

[4]	Path Optimization for Line Scanning on Flat Panel Displays Using a Self Organizing Map
	Computational Research, 2014

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