Research on Defect Recognition Method of Digital Pipeline Negatives Based on Improved YOLO Algorithm-Reference-Cited by-同舟云学术

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Research on Defect Recognition Method of Digital Pipeline Negatives Based on Improved YOLO Algorithm

Published:2023-12-01 Issue: Volume:21 Page:980-985
ISSN:
Container-title:2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI)
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Author:

Luo Weijian¹,Deng Cong¹,Liu Jiayue¹,Li Xufeng¹

Affiliation:

1. Guangdong Institute of Special Equipment Inspection and Research,Guangzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10488913/10488921/10489401.pdf?arnumber=10489401

Reference20 articles.

1. A Review of the Object Detection Algorithm Based on Deep Learning[J];Wenqing;Science & Technology Information,2023

2. Review of YOLO Algorithm Based on Small Target Detection[J];Chengjia;Journal of Jilin Engineering Normal University,2023

3. Main Issues on the Seismic Design of Industrial Piping Systems and Components[C];Fabriziopaolacci,2013

4. Intelligent Automation to Oil & Gas Pipeline Inspections[J];Pan;Fiber Optic Sensors & Systems,2022

5. Research on X-ray Weld Defects Detection by Deep CNN[J];Liu;Transducer and Microsystem Technologies,2018

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