Computer Vision Algorithm for Predicting the Welding Efficiency of Friction Stir Welded Copper Joints from its Microstructures
This research paper presents a study of the prediction of Friction Stir Welded (FSW) joint effectiveness using microstructure images with the aid of Convolutional Neural Networks (CNNs). A total of 3000 microstructure pictures were used for training the CNN, and 300 new microstructure photographs we...
Main Authors: | Mishra Akshansh, Jatti Vijaykumar S., Suman Asmita, Dixit Devarrishi |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2023-01-01
|
Series: | E3S Web of Conferences |
Subjects: | |
Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01252.pdf |
Similar Items
-
Machine Learning Algorithm for Surface Quality Analysis of Friction Stir Welded Joint
by: Mishra Akshansh
Published: (2020-11-01) -
Discrete Wavelet Transformation Approach for Surface Defects Detection in Friction Stir Welded Joints
by: Mishra Akshansh
Published: (2020-12-01) -
Welding defects at friction stir welding
by: P. Podržaj, et al.
Published: (2015-04-01) -
Fatigue in Friction Stir Welding /
by: Jordon, J. Brian, author 648506, et al.
Published: (2019) -
Assessment Of Joints Using Friction Stir Welding And Refill Friction Stir Spot Welding Methods
by: Lacki P., et al.
Published: (2015-09-01)