News
Happy to present our paper titled ‘Quantitative Performance Analysis of Machine Learning Model from Discrete Perspective: A Case Study of Chip Detection in Turning Process’ in ’15th International Conference on Agents and Artificial Intelligence (ICAART2023)’.
Another journal paper, Q2 ranked (Engineering, Multidisciplinary) , 2.679 impact factor.
Thanks to all the Authors.
“Dear Authors,
We are pleased to inform you that your article “Machine-Learning-Based
Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary
Overview” has been published in Applied Sciences as part of the Special Issue
Artificial Intelligence and Optimization in Industry 4.0 and is available
PDF Version: https://lnkd.in/e2FWs9DA
Conference Paper on ‘Explainable Machine Learning to Improve Assembly Line Automation (Dec 2021)’ by
Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum, Michael Osbakk at
4th International Conference on Artificial Intelligence for Industries (ai4i 2021)
General assembly meeting on 23rd September
Robin Andersson Dickfors, and Nick Grannas are presenting their thesis work on ‘OBJECT DETECTION USING DEEP LEARNING ON METAL CHIPS IN MANUFACTUR ‘ through the DIGICOGS project.
Examiner: Shahina Begum, Mälardalen University, Västerås, Sweden
Supervisors: Mobyen Uddin Ahmed, Sharmin Sultana Sheuly, Mälardalen University, Västerås, Sweden
Our 4th General assembly meeting on 20th April
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