Leaky Cable Fixture Detection in Railway Tunnel Based on RW DCGAN and Compressed GS-YOLOv5-Reference-Cited by-同舟云学术

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Leaky Cable Fixture Detection in Railway Tunnel Based on RW DCGAN and Compressed GS-YOLOv5

Published:2023 Issue:1 Volume:37 Page:1163-1180
ISSN:1079-8587
Container-title:Intelligent Automation & Soft Computing
language:en
Short-container-title:

Author:

Li Suhang,Zhang Yunzuo,Liu Ruixue,Zhang Jiayu,Song Zhouchen,Wang Yutai

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

https://www.techscience.com/iasc/v37n1/52694/pdf

Reference36 articles.

1. A system-level performance evaluation for a 5g system under a leaky coaxial cable MIMO channel for high-speed trains in the railway tunnel;Liu;Electronics,2022

2. YOLOv5-tassel: Detecting tassels in RGB UAV imagery with improved YOLOv5 based on transfer learning;Liu;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2022

3. YOLOv5_CSL_F: YOLOv5’s loss improvement and attention mechanism application for remote sensing image object detection;Wang,2021

4. Gas cylinder detection using deep learning based YOLOv5 object detection method;Albayrak,2022

5. A distributed FMCW radar system based on fiber-optic links for small drone detection;Shin;IEEE Transactions on Instrumentation and Measurement,2017

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