A Fabric Defect Detection Method Based on Improved YOLOv5-Reference-Cited by-同舟云学术

A Fabric Defect Detection Method Based on Improved YOLOv5

Published:2021-12-10 Issue: Volume: Page:
ISSN:
Container-title:2021 7th International Conference on Computer and Communications (ICCC)
language:
Short-container-title:

Author:

Zheng Liaomo,Wang Xiaojie,Wang Qi,Wang Shiyu,Liu Xinjun

Funder

National Key Research and Development Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9674217/9674209/09674548.pdf?arnumber=9674548

Reference16 articles.

1. YOLOv5: v3.1 - Bug Fixes and Performance Improvements;jocher,0

2. Cbam: Convolutional block attention module;woo;Proceedings of the European Conference on Computer Vision (ECCV),2018

3. Squeeze-and-Excitation Networks;hu;IEEE Transactions on Pattern Analysis and Machine Intelligence,2020

4. Rectified Linear Units Improve Restricted Boltzmann Machines;nair;Proceedings of the 24th International Conference on Machine Learning(ICML),2010

5. Rectifier nonlinearities improve neural network acoustic models;maas;Proceedings of the 24th International Conference on Machine Learning(ICML),2013

Cited by 19 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. Automated fabric defect detection using hybrid particle cat swarm optimizer with deep learning model;Multimedia Tools and Applications;2024-02-02

2. High-Speed and Accurate Cascade Detection Method for Chip Surface Defects;IEEE Transactions on Instrumentation and Measurement;2024

3. Steel surface defect detection algorithm using deep learning;International Conference on Internet of Things and Machine Learning (IoTML 2023);2023-11-29

4. An Improved YOLOv5s for Detecting Glass Tube Defects;Communications in Computer and Information Science;2023-11-26

5. Lightweight Single Shot Multi-Box Detector: A fabric defect detection algorithm incorporating parallel dilated convolution and dual channel attention;Textile Research Journal;2023-10-14