PCB bare board defect detection based on improved YOLOv5s-Reference-Cited by-同舟云学术

PCB bare board defect detection based on improved YOLOv5s

Published:2023-09-22 Issue: Volume: Page:
ISSN:
Container-title:2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)
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Author:

Jin Yuxin¹,Cai Lecai²,Cheng Kui²,Wang Xinjie¹,Luo Chunlan¹,Jiao Sanxiu¹

Affiliation:

1. Sichuan University of Science & Engineering Sanjiang Artificial Intelligence and Robot Research Institute, Yibin University,School of Automation and Information Engineering,Yibin,China

2. Yibin University,Sanjiang Artificial Intelligence and Robot Research Institute,Yibin,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10295546/10295577/10295682.pdf?arnumber=10295682

Reference13 articles.

1. TDD‐net: a tiny defect detection network for printed circuit boards

2. Omni-dimensional dynamic convolution[J];li,2022

3. Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

4. BiFormer: Vision Transformer with Bi-Level Routing Attention

5. PCB defect detection based on improved YOLOv4 algorithm[J];li;Electronic Measurement Technology,2021

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