Overview: Computer Vision and Machine Learning for Microstructural Characterization and Analysis-Reference-Cited by-同舟云学术

Overview: Computer Vision and Machine Learning for Microstructural Characterization and Analysis

Published:2020-09-29 Issue:12 Volume:51 Page:5985-5999
ISSN:1073-5623
Container-title:Metallurgical and Materials Transactions A
language:en
Short-container-title:Metall Mater Trans A

Author:

Holm Elizabeth A.,Cohn Ryan,Gao Nan,Kitahara Andrew R.,Matson Thomas P.,Lei Bo,Yarasi Srujana Rao

Publisher

Springer Science and Business Media LLC

Subject

Metals and Alloys,Mechanics of Materials,Condensed Matter Physics

Link

https://link.springer.com/content/pdf/10.1007/s11661-020-06008-4.pdf

Reference128 articles.

1. C. S. Smith: A History of Metallography: The Development of Ideas on the Structure of Metals before 1890. (MIT Press, Cambridge, MA, 1988), pp. 1-314.

2. H. C. Sorby, J. Iron and Steel Institute 1887, vol. 37, pp. 255-288.

3. G. F. Vander-Voort, Standardization News 1991, vol. 19, pp. 42-47.

4. University of Cambridge DoITPoMS: Micrograph Library http://www.doitpoms.ac.uk/miclib/index.php (2004–2013), http://www.doitpoms.ac.uk/miclib/index.php. Accessed 9 Aug 2020.

5. B.L. DeCost, M. D. Hecht, T. Francis, Y. N. Picard, B. A. Webler and E. A. Holm, Integr. Mater. Manuf. Innov. 2017, vol. 6, pp. 197-205.

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