Detection Model of Drainage Pipe Defect Based on Improved YOLOv5-Reference-Cited by-同舟云学术

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Detection Model of Drainage Pipe Defect Based on Improved YOLOv5

Published:2023-04-21 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Intelligent Computing and Signal Processing (ICSP)
language:
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Author:

Jia Pengtao¹,Guo Tong¹,Guo Fengjing²,Wang Bin³,Xiong Qi³

Affiliation:

1. Xi’an University of Science and Technology,College of Computer Science and Technology,Xi’an,China

2. Shaanxi Shaanxi Coal Pu Bai Mining Co,Board of Directors,Xi’an,China

3. Shaanxi Jianxin Coal Chemical Co,Communication and Defense Department,Xi’an,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10248366/10248210/10248934.pdf?arnumber=10248934

Reference15 articles.

1. YOLOv3: An Incremental Improvement[J];redmon,2018

2. YOLO9000: Better, Faster, Stronger

3. Drainage pipe defect detection and identification by fusing RFB-SE depth model;jia,2022

4. YOLOv4: Optimal Speed and Accuracy of Object Detection[J];bochkovskiy,2020

5. You Only Look Once: Unified, RealTime Object Detection;redmon;2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016

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