FN-Net: A lightweight CNN-based architecture for fabric defect detection with adaptive threshold-based class determination-Reference-Cited by-同舟云学术

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FN-Net: A lightweight CNN-based architecture for fabric defect detection with adaptive threshold-based class determination

Published:2022-07 Issue: Volume:73 Page:102241
ISSN:0141-9382
Container-title:Displays
language:en
Short-container-title:Displays

Author:

Suryarasmi Anindita^ORCID,Chang Chin-Chun^ORCID,Akhmalia Rania,Marshallia Maysa,Wang Wei-Jen^ORCID,Liang Deron^ORCID

Funder

Institute for Information Industry, Ministry of Science and Technology, Taiwan

Ministry of Economic Affairs

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Human-Computer Interaction

Reference28 articles.

1. Fabric defect detection systems and methods—a systematic literature review;Hanbay;Optik,2016

2. A visual long-short-term memory based integrated CNN model for fabric defect image classification;Zhao;Neurocomputing,2020

3. Computer vision based detection of external defects on tomatoes using deep learning;da Costa;Biosyst. Eng.,2020

4. DLSE-Net: A robust weakly supervised network for fabric defect detection;Liu;Displays,2021

5. Automated fabric defect detectionA review;Ngan;Image Vis. Comput.,2011

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5. Lightweight Detection of Metal Workpieces Based on YOLOv8;2024 5th International Conference on Computer Vision, Image and Deep Learning (CVIDL);2024-04-19

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