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Hasan-Ur Rahman

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Articles

Machine Learning-Assisted Raman Spectroscopy and SERS for Bacterial Pathogen Detection: Clinical, Food Safety, and Environmental Applications

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By Hasan-Ur Rahman, Manoj Tripathi, Mahzuzah Zahan, Tao Ye
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Automated Crack Detection in 2D Hexagonal Boron Nitride Coatings Using Machine Learning

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By Etienne Z. Gnimpieba, Venkataramana Gadhamshetty, Hasan-Ur Rahman, Bharat K. Jasthi
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Open in Who Shared Issue with article?

Automated Crack Detection in 2D Hexagonal Boron Nitride Coatings Using Machine Learning

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By Hasan-Ur Rahman, Bharat K. Jasthi, Etienne Z. Gnimpieba, Venkataramana Gadhamshetty
| brnw.ch
4. Discussion The results presented demonstrate the YOLOv8n model’s potential for crack detection in CVD-grown hBN. Its ability to identify cracks of varying sizes and complexities aligns with the urgent need for streamlined, automated characterization methods in the field of 2D materials. The model’s performance, particularly in detecting diverse crack types, underscores the capabilities of machine learning techniques to address the limitations of traditional optical characterization approaches.
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