Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

This comment is on “Machine learning enhanced analysis of EBSD data for texture representation” by Wanni, J., Bronkhors, C. A. & Thoma, D. J. npj Comput. Mater. 10, 133 (2024), https://doi.org/10.1038/s41524-024-01324-4 . The authors’ proof of concept and validation of their approach to texture representation are severely corrupted, its application may lead to false conclusions.

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Publication Details

Journal
npj Computational Materials
Published
2025-03-19
DOI
https://doi.org/10.1038/s41524-025-01557-x
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

Helmut Schaeben, K. Gerald van den Boogaart
npj Computational Materials
Radiomics and Machine Learning in Medical Imaging
article

Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

Helmut Schaeben, K. Gerald van den Boogaart
article en

Abstract

This comment is on “Machine learning enhanced analysis of EBSD data for texture representation” by Wanni, J., Bronkhors, C. A. & Thoma, D. J. npj Comput. Mater. 10, 133 (2024), https://doi.org/10.1038/s41524-024-01324-4 . The authors’ proof of concept and validation of their approach to texture representation are severely corrupted, its application may lead to false conclusions.

npj Computational MaterialsVol. 11(1)
Helmholtz-Zentrum Dresden-Rossendorf (DE), Helmholtz Institute Freiberg for Resource Technology (DE), TU Bergakademie Freiberg (DE)
Openalex Percentile: Top 92%
Radiomics and Machine Learning in Medical Imaging
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