Towards Fast Edge Detection Approach for Industrial Products-Reference-Cited by-同舟云学术

Towards Fast Edge Detection Approach for Industrial Products

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 21st International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS)
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Author:

Honi Dhafer G.¹,Ali Ali Hasan¹,Abduljabbar Zaid Ameen¹,Ma Junchao²,Nyangaresi Vincent Omollo³,Mutlaq Keyan Abdul-Aziz⁴,Umran Samir M.⁵

Affiliation:

1. University of Basrah,College of Education for Pure Sciences,Basrah,Iraq,61004

2. Shenzhen Technology University,College of Big Data and Internet,Shenzhen,China,518118

3. Tom Mboya University,Faculty of Biological and Physical,Homabay,Kenya,40300

4. University of Basrah,It and Communication center,Basrah,Iraq,61004

5. Huazhong University of Science and Technology,School of Cyber Science and Engineering,Wuhan,China,430047

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10085978/10086056/10086271.pdf?arnumber=10086271

Reference43 articles.

1. Pixel-wise deep learning for contour detection;hwang;arXiv 1504 01989,2015

2. Multiregional Segmentation of High-Grade Glioma Using Modified Deep UNET Model with Edge-Detected Multimodal MRI Images;gore;Cyber Intelligence and Information Retrieval,2021

3. DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection

4. Screening of breast cancer from thermogram images by edge detection aided deep transfer learning model

5. Image Edge Detection: A New Approach Based on Fuzzy Entropy and Fuzzy Divergence

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