@inproceedings{d0805d3c69a24100a6f9b5273cf48233,
title = "Automatic visual inspection and classification based on rough sets and neural network",
abstract = "In this paper, a novel visual inspection and classification technology based on rough sets and neural network algorithm is presented. The rough set algorithm of data classification is discussed. As a large quantity of ambiguous and redundant data can be removed effectively using rough set theory, training time of neural networks is further decreased and the classification accuracy is also improved. Combined with anti-disturbance of the neural network, the effectiveness of classification technology is performed for the defect inspection of wood veneer with its rapid classification capacity and high classification accuracy.",
keywords = "Classification, Defect, Neural network, Rough sets, Visual inspection",
author = "Li, {Meng Xin} and Wu, {Cheng Dong} and Yong Yue",
year = "2003",
language = "English",
isbn = "0780378652",
series = "International Conference on Machine Learning and Cybernetics",
pages = "3095--3099",
booktitle = "International Conference on Machine Learning and Cybernetics",
note = "2003 International Conference on Machine Learning and Cybernetics ; Conference date: 02-11-2003 Through 05-11-2003",
}