An Accurate Defect Detection Model for Photosensitive Elements Based on Improved YOLOV4 Deep Neural Network-Reference-Cited by-同舟云学术

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An Accurate Defect Detection Model for Photosensitive Elements Based on Improved YOLOV4 Deep Neural Network

Published:2022-08-19 Issue: Volume: Page:
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Container-title:2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
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Author:

Yu Mingqi¹,Yue Hongwei²,Chen Chuangquan¹,Zhou Cong³,Huang Yufeng¹,Wang Dong¹,Deng Fuqin⁴

Affiliation:

1. Wuyi University,Faculty of Intelligent Manufacturing,Jiangmen,China,529020

2. Faculty of Intelligent Manufacturing Wuyi University, Jiangmen 529020

3. Silicool Technology (Zhuhai) Ltd., Zhuhai, China

4. Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China

Funder

Shenzhen Peacock Plan

Natural Science Foundation of Guangdong Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9904023/9904007/09904176.pdf?arnumber=9904176

Reference35 articles.

1. Centernet: Keypoint triplets for object detection;duan;Proceedings of the IEEE/CVF International Conference on Computer Vision,2019

2. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

3. EfficientDet: Scalable and Efficient Object Detection

4. A Robust Fabric Defect Detection Method Based on Improved RefineDet

5. Feature Pyramid Networks for Object Detection

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Improved YOLOv8 Network for Photosensitive Element Defect Detection;2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI);2023-08-18

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