An end-to-end computer vision methodology for quantitative metallography

Matan Rusanovsky, Ofer Beeri, Gal Oren

Open source

DOI: 10.1038/s41598-022-08651-w
Published: 2022-03-21
Container: Scientific Reports
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-022-08651-w,
  title = {An end-to-end computer vision methodology for quantitative metallography},
  author = {Matan Rusanovsky and Ofer Beeri and Gal Oren},
  year = {2022},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-022-08651-w},
  url = {https://doi.org/10.1038/s41598-022-08651-w}
}

RIS

TY  - JOUR
TI  - An end-to-end computer vision methodology for quantitative metallography
AU  - Matan Rusanovsky
AU  - Ofer Beeri
AU  - Gal Oren
PY  - 2022
JO  - Scientific Reports
DO  - 10.1038/s41598-022-08651-w
UR  - https://doi.org/10.1038/s41598-022-08651-w
ER  -

APA

Rusanovsky, M., Beeri, O., & Oren, G. (2022). An end-to-end computer vision methodology for quantitative metallography. Scientific Reports. https://doi.org/10.1038/s41598-022-08651-w

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crossref · retrieved 2026-09-26T20:01:14.500Z