Automated Defect Detection in Electronic Components using Convolutional Neural Networks-Reference-Cited by-同舟云学术

Automated Defect Detection in Electronic Components using Convolutional Neural Networks

Published:2024-04-04 Issue: Volume:65 Page:1-6
ISSN:
Container-title:2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
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Author:

Shobanadevi A.¹,Kottu Sreekanth²,Kumar K R Senthil³,Amudha K.⁴,Praveena K.⁵,Venkatesh R.⁶

Affiliation:

1. School of Computing, SRM Institute of Science and Technology,Department of Data Science and Business Systems,Chennai,Tamil Nadu,India,600026

2. Mallareddy University,Department of Computer Science & Engineering,Hyderabad,Telangana,India,500043

3. R.M.K. Engineering College,Department of Mechanical Engineering,Kavaraipettai,Tamil Nadu,India,601206

4. R.M.D. Engineering College (An Autonomous Institution),Department of Science and Humanities-Physics,Kavaraipettai,Tamil Nadu,India,601206

5. Mohan Babu University, Erstwhile SreeVidyanikethan Engineering College,Department of Electronics and Communication Engineering,Andhra Pradesh,India,517102

6. PSNA College of Engineering and Technology (Autonomous),Department of Physics,Dindigul,Tamil Nadu,India,624622

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10568576/10568577/10568637.pdf?arnumber=10568637

Reference13 articles.

1. Automated defect detection in electronic components using convolutional neural networks;Zhang;IEEE Trans. Ind. Electron.,2018

2. Study of the performance signature based ternary and quaternary III–V compounds for laser diodes in optical communication system

3. Detection of bare PCB defects by image subtraction method using machine vision;Chauhan,2011

4. Automated defect detection in electronic components using transfer learning;Chen;IEEE Trans. Reliab.,2021

5. A novel approach to automated defect detection in electronic components using deep learning;Kim;IEEE Trans. Compon., Packag., Manuf. Technol.,2021