Comparison of Algorithm and Kernel Accuracy in Defect Detection Using Pressure in Sleeve Soldering Equipment-Reference-Cited by-同舟云学术

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Comparison of Algorithm and Kernel Accuracy in Defect Detection Using Pressure in Sleeve Soldering Equipment

Published:2024-01-12 Issue: Volume: Page:412-417
ISSN:
Container-title:2024 8th International Conference on Robotics, Control and Automation (ICRCA)
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Author:

Watanabe Kan¹,Uwano Hidetake²,Fukuoka Hiroshi³

Affiliation:

1. National Institute of Technology (KOSEN), Nara College,Department of Advanced Information Engineering,Nara,Japan

2. National Institute of Technology (KOSEN), Nara College,Department of Information Engineering,Nara,Japan

3. National Institute of Technology (KOSEN), Nara College,Department of Mechanical Engineering,Nara,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10648987/10648988/10649389.pdf?arnumber=10649389

Reference14 articles.

1. Defect Classification using Pressure Change of Sleeve Soldering Machine

2. Solder joint defect classification based on ensemble learning

3. Soldering defect detection in automatic optical inspection

4. Automatic First Arrival Picking on P-Wave Seismic Signal Using Support Vector Machine Method

5. Cuffless blood pressure prediction from PPG using relevance vector machine

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