Fabric surface defect classification and systematic analysis using a cuckoo search optimized deep residual network-Reference-Cited by-同舟云学术

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Fabric surface defect classification and systematic analysis using a cuckoo search optimized deep residual network

Published:2024-05 Issue: Volume:53 Page:101681
ISSN:2215-0986
Container-title:Engineering Science and Technology, an International Journal
language:en
Short-container-title:Engineering Science and Technology, an International Journal

Author:

Mewada Hiren^ORCID,Pires Ivan Miguel^ORCID,Engineer Pinalkumar^ORCID,Patel Amit V.

Funder

Fundação para a Ciência e a Tecnologia

Ministério da Educação e Ciência

Ministerio de Educación, Cultura y Deporte

European Regional Development Fund

Publisher

Elsevier BV

Reference54 articles.

1. Defective and nondefective classif ication of fabric images using shallow and deep networks;Elemmi;Int. J. Intell. Syst.,2022

2. Identifying defective solar cells in electroluminescence images using deep feature representations;Al-Waisy;PeerJ Comput. Sci.,2022

3. Fabric defect segmentation method based on deep learning;Huang;IEEE Trans. Instrum. Meas.,2021

4. Effective textile quality processing and an accurate inspection system using the advanced deep learning technique;Jeyaraj;Text. Res. J.,2020

5. Fabric defect detection using competitive cat swarm optimizer based RideNN and deep neuro Fuzzy network;Biradar;Sens. Imaging,2022

Cited by 1 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. MSIDetector: Detecting Multi-Scenario industrial defects using an adapted visual foundation model and dual thresholding discriminator;Measurement;2024-09

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