An automated defect detection method for optimizing industrial quality inspection-Reference-Cited by-同舟云学术

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An automated defect detection method for optimizing industrial quality inspection

Published:2024-01 Issue: Volume:127 Page:107387
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wang Congcong,Wei Xiumei,Jiang Xuesong

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference41 articles.

1. Saliency-based defect detection in industrial images by using phase spectrum;Bai;IEEE Trans. Ind. Inform.,2014

2. Yolov4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

3. Cascade r-cnn: Delving into high quality object detection;Cai,2018

4. RetinaNet with difference channel attention and adaptively spatial feature fusion for steel surface defect detection;Cheng;IEEE Trans. Instrum. Meas.,2020

5. Fabric defect detection algorithm based on PHOG and SVM;Cuifang;Indian J. Fibre Text. Res. (IJFTR),2020

Cited by 2 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. DFFNet: a lightweight approach for efficient feature-optimized fusion in steel strip surface defect detection;Complex & Intelligent Systems;2024-06-20

2. Faster Region Convolutional Neural Network with Attentional Feature Fusion for Small Defect Detection;2024

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