A Deep Convolutional Generative Adversarial Networks-Based Method for Defect Detection in Small Sample Industrial Parts Images

A Deep Convolutional Generative Adversarial Networks-Based Method for Defect Detection in Small Sample Industrial Parts Images

Online defect detection in small industrial parts is of paramount importance for building closed loop intelligent manufacturing systems. However, high-efficiency and high-precision detection of surface defects in these manufacturing systems is a difficult task and poses a major research challenge. T...

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Bibliographic Details
Main Authors:	Gao, H. (Author), Lv, W. (Author), Qasim, T. (Author), Wang, D. (Author), Yin, J. (Author), Zhang, Y. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	data augmentation deep convolution generation adversarial network defect detection lightweight model
Online Access:	View Fulltext in Publisher

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