Enhancing Materials Science through Computer Image Analysis and IQA Approaches

Enhancing Materials Science through Computer Image Analysis and IQA Approaches


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Abstract. Computer image analysis allows for various object detection and classification as well as conducting measurements on microscope images. Technological development, including the application of artificial intelligence solutions, speeds up the classification of large data sets. In the context of image analysis, an essential issue is image quality assessment (IQA). Applying the tools of image analysis, or artificial intelligence, linked with the appropriate IQA approach reveals the opportunity to develop materials with better functional and technological properties more sustainably and effectively.

Image Analysis, Materials Science, Microstructure, Image Quality Assessment, Machine Learning

Published online 9/1/2023, 6 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: PIWOWARCZYK Adam, JASTRZĘBSKA Ilona, Enhancing Materials Science through Computer Image Analysis and IQA Approaches, Materials Research Proceedings, Vol. 34, pp 374-379, 2023

DOI: https://doi.org/10.21741/9781644902691-43

The article was published as article 43 of the book Quality Production Improvement and System Safety

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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