Analysis of Optimizer Effects on CNN Model for Defect Identification in Welding Results of A 106 Grade B Carbon Steel Pipe-Reference-Cited by-同舟云学术

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Analysis of Optimizer Effects on CNN Model for Defect Identification in Welding Results of A 106 Grade B Carbon Steel Pipe

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Electrical Engineering and Informatics (ICEEI)
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Author:

Al Amin Mochammad Karim¹,Wahyudi Mohammad Thoriq¹,Yaqin Muhammad Ainul²,Adhitya Ryan Yudha²,Anggara Dika¹,Alliyrahmanda Aygasta Firstya¹,Munir Moh Miftachul¹,Septian Eka Cahya³

Affiliation:

1. Welding Engineering Study Program, Shipbuilding Institute Polytechnic of Surabaya,Surabaya,Indonesia

2. Automation Engineering Study Program, Shipbuilding Institute Polytechnic of Surabaya,Surabaya,Indonesia

3. PT. Kintomo Engineering Group,Surabaya,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10346236/10346214/10346872.pdf?arnumber=10346872

Reference20 articles.

1. Weld Defect Detection and Classification based on Deep Learning Method: A Review;Purnomo;J. Ilmu Komput. dan Inf. (Journal Comput. Sci. Information),2023

2. Determination of ‘Excessive Penetration’ Height on Pipes using Film Density Variation Method,” Penentuan Tinggi “Excessive Penetration;Sutrasno;pada Pipa dengan Metod.,2018

3. Classification of Defects in Welds Using a Convolution Neural Network

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