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Automated Optical Inspection Method for Light-Emitting Diode Defect Detection Using Unsupervised Generative Adversarial Neural Network

Published:

November 22, 2021

Author:

Che-Hsuan Huang, Pei-Hsuan Lee, Shu-Hsiu Chang, Hao-Chung Kuo, Chia-Wei Sun, Chien-Chung Lin, Chun-Lin Tsai and Xinke Liu

Abstract:

Many automated optical inspection (AOI) companies use supervised object detection networks to inspect items, a technique which expends tremendous time and energy to mark defectives. Therefore, we propose an AOI system which uses an unsupervised learning network as the base algorithm to simultaneously generate anomaly alerts and reduce labeling costs. This AOI system works by deploying the GANomaly neural network and the supervised network to the manufacturing system. To improve the ability to distinguish anomaly items from normal items in industry and enhance the overall performance of the manufacturing process, the system uses the structural similarity index (SSIM) as part of the loss function as well as the scoring parameters. Thus, the proposed system will achieve the requirements of smart factories in the future (Industry 4.0)....

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Company Information:

Shenzhen University

Shenzhen University is a public research university located in Nanshan district, Shenzhen, Guangdong, China. It is accredited by the State Council of the People's Republic of China and is funded by the Shenzhen City Government.

Shenzhen, Guangdong Province, China

School

  • Phone +86 755 2653 6114

Shenzhen University website

Company Postings:

(1) technical library article

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