research-article

PCB Micro-Soldering Status Inspection System Research based on Deep Learning

Authors:

JaeChang Shim,

YeongSeo Ha,

JiHee Park,

Yeunghak LeeAuthors Info & Claims

AICCC '22: Proceedings of the 2022 5th Artificial Intelligence and Cloud Computing Conference

Pages 29 - 33

https://doi.org/10.1145/3582099.3582104

Published: 20 April 2023 Publication History

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Abstract

In the semiconductor process, the soldering state is one of the important processes. This error can be one of the main causes of fatal effects on other electronic components. Until now, all soldering status have been inspected by humans. This causes many false positive errors. This study experimented with micro-soldering status inspection using artificial intelligence which has 1-stage and 2-stage compound scaling. As a result of the experiment, PCB-soldering condition inspection showed low false positives in 1-stage detector (YOLOv5) unlike other objects.

References

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AICCC '22: Proceedings of the 2022 5th Artificial Intelligence and Cloud Computing Conference

December 2022

302 pages

ISBN:9781450398749

DOI:10.1145/3582099

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 20 April 2023

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AICCC 2022

AICCC 2022: 2022 5th Artificial Intelligence and Cloud Computing Conference

December 17 - 19, 2022

Osaka, Japan

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