Tong Yang - IEEE Xplore Author Profile
Access provided by:

MIT Libraries

Sign Out
Access provided by:

MIT Libraries

Sign Out
ADVANCED SEARCH

Author details

< Back

Tong Yang

Publications
3
Citations
0
Publications by Year
20232024
Co-Authors:
Show All Co-Authors (18)
Image of author Tong Yang

Tong Yang

Affiliation

Faculty of Transportation Engineering
Kunming University of Science and Technology
Kunming, Yunnan, China

Publication Topics

Biography

Tong Yang received the B.E. degree from Kunming University of Science and Technology, Kunming, China, in 2022, where he is currently pursuing the master’s degree.,His research interests include data mining and deep learning.(Based on document published on 12 September 2024).
Publications
3
Citations
0
Publications by Year
20232024
Co-Authors:
Show All Co-Authors (18)
Author's Published Works

Showing 1-3 of 3 results

  • Sort

Filter Results

Show

Sort By

Results

GPR Imagery-Based Internal Defect Evaluation System for Railroad Tunnel Lining Using Real-Time Instance Segmentation

Sihui Long;Tong Yang;Yu Qian;Yunpeng Wu;Fei Xu;Qingjingyi Tang;Fengxiang Guo

IEEE Sensors Journal
Year: 2024 | Volume: 24, Issue: 21 | Journal Article |
Railroad tunnel linings may have voids filled with water or air, or areas that lack compaction due to construction processes. These structural defects are hard to detect and require regular inspections to ensure safety. Existing convolutional neural network (CNN)-based inspection systems that employ ground-penetrating radar (GPR) imagery sometimes cannot fully assess the defects and ensure the str...Show More

GPR Imagery-Based Internal Defect Evaluation System for Railroad Tunnel Lining Using Real-Time Instance Segmentation

Sihui Long;Tong Yang;Yu Qian;Yunpeng Wu;Fei Xu;Qingjingyi Tang;Fengxiang Guo

Year: 2024 | Volume: 24, Issue: 21 | Journal Article |

A CNN-Based Automatic Detection Method for Tunnel Lining Internal Defect Using Ground Penetrating Radar

Tong Yang;Jingyi Tangqing;Guangcai Zhang;Sihui Long;Fengxiang Guo;Fei Xu;Zheyi Chen;Yunpeng Wu

2023 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC)
Year: 2023 | Conference Paper |
Regular tunnel lining internal damage (TLID) inspection is very crucial for the railroad operation safety. However, traditional manual identification methods using ground penetrating radar (GPR) images suffer from limited accuracy and efficiency. Fortunately, CNN-based automatic inspection methods have the potential to replace manual inspections, offering improved precision and productivity. In th...Show More

A CNN-Based Automatic Detection Method for Tunnel Lining Internal Defect Using Ground Penetrating Radar

Tong Yang;Jingyi Tangqing;Guangcai Zhang;Sihui Long;Fengxiang Guo;Fei Xu;Zheyi Chen;Yunpeng Wu

Year: 2023 | Conference Paper |

Printed Circuit Board Defect Detection Based on Improved YOLOv5

Tong Yang;Yuguo Liu;Changxin Jin;Kai Jiang;Qiang Duan;Chen Song;Qibin Chen;Xue Li;Junzheng Ge;Rui Li

2023 6th International Conference on Information and Computer Technologies (ICICT)
Year: 2023 | Conference Paper |
Aiming at the problems of low efficiency and poor real-time performance in the printed circuit board (PCB) defect detection, a PCB defect detection method based on the improved YOLOv5 is proposed, which integrates the module of multiscale detection, attention mechanism and multi-branch. A shallow detection layer is added to detect smaller defect targets and fused with features of the deep network....Show More

Printed Circuit Board Defect Detection Based on Improved YOLOv5

Tong Yang;Yuguo Liu;Changxin Jin;Kai Jiang;Qiang Duan;Chen Song;Qibin Chen;Xue Li;Junzheng Ge;Rui Li

Year: 2023 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.