Enhancing Battery Exterior Defect Inspection Accuracy Through Defect-Background Separated GAN Development

This paper aims to develop a defect-background separated generative adversarial network (GAN) using deep learning and GAN to enhance the accuracy of battery exterior defect inspection. In actual battery production lines, the occurrence rates of defects vary by defect type, making it challenging to c...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Donghun Ku, Heui Jae Pahk
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Subjects:	Battery exterior defect inspection deep learning defect segmentation generative adversarial network synthetic defect
Online Access:	https://ieeexplore.ieee.org/document/10477991/