Automated Surface Defect Detection in Metals: A Comparative Review of Object Detection and Semantic Segmentation Using Deep Learning-Reference-Cited by-同舟云学术

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Automated Surface Defect Detection in Metals: A Comparative Review of Object Detection and Semantic Segmentation Using Deep Learning

Published:2022-05 Issue:3 Volume:58 Page:4203-4213
ISSN:0093-9994
Container-title:IEEE Transactions on Industry Applications
language:
Short-container-title:IEEE Trans. on Ind. Applicat.

Author:

Usamentiaga Ruben¹^ORCID,Lema Dario G.¹^ORCID,Pedrayes Oscar D.¹^ORCID,Garcia Daniel F.¹^ORCID

Affiliation:

1. Department of Computer Science, Engineering, University of Oviedo, Gijón, Spain

Funder

Spanish National Plan for Research, Development and Innovation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/28/9778222/09713940.pdf?arnumber=9713940

Reference24 articles.

1. Image Segmentation Using Deep Learning: A Survey

2. YOLOV4: Optimal speed and accuracy of object detection;bochkovskiy,2020

3. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Int Conf Med Image Comput Comput - Assist Interv,0

4. The history began from AlexNet: A comprehensive survey on deep learning approaches;alom,2018

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