Weld Image Evaluation Model Using Improved Loss Function-Reference-Cited by-同舟云学术

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Weld Image Evaluation Model Using Improved Loss Function

Published:2023-08-09 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 16th International Conference on Electronic Measurement & Instruments (ICEMI)
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Author:

Wang Zhihao¹,Zhang Chi²,Dang Zenglin³,Sun Zhengxiang⁴,Chen Haotian³,Tang Qingyu⁴,Sun Haoran⁵,Liu Zhijian³

Affiliation:

1. Dalian maritime university, College Of Marine Electrical Engineering,Dalian,China

2. Dalian maritime university, Transportation Engineering College,Dalian,China

3. Dalian maritime university, Marine Engineering College,Dalian,China

4. Dalian maritime university, Information Science and Technology College,Dalian,China

5. Dalian maritime university,Maritime Economics and Management,Dalian,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10269800/10269827/10270732.pdf?arnumber=10270732

Reference14 articles.

1. Deep Learning-Based Detection of Penetration from Weld Pool Reflection Images

2. End-to-end prediction of weld penetration: A deep learning and transfer learning based method

3. Weld image deep learning-based on-line defects detection using convolutional neural networks for Al alloy in robotic arc welding

4. Real-Time Detection of Weld Defects for Automated Welding Process Base on Deep Neural Network

5. Automatic Detection of Welding Defects Using Faster R-CNN

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