Machine learning to analyze images of shocked materials for precise and accurate measurements
- Authors:
-
[1];
[3];
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA, Institute for Soldier Nanotechnology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Nevada National Security Site, North Las Vegas, Nevada 89030, USA
- Los Alamos National Laboratories, Los Alamos, New Mexico 87545, USA
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1390398
- Grant/Contract Number:
- 25946-3183; AC52-06NA25396
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Journal of Applied Physics
- Additional Journal Information:
- Journal Name: Journal of Applied Physics Journal Volume: 122 Journal Issue: 10; Journal ID: ISSN 0021-8979
- Publisher:
- American Institute of Physics
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Dresselhaus-Cooper, Leora, Howard, Marylesa, Hock, Margaret C., Meehan, B. T., Ramos, Kyle J., Bolme, Cindy A., Sandberg, Richard L., and Nelson, Keith A. Machine learning to analyze images of shocked materials for precise and accurate measurements. United States: N. p., 2017.
Web. doi:10.1063/1.4998959.
Dresselhaus-Cooper, Leora, Howard, Marylesa, Hock, Margaret C., Meehan, B. T., Ramos, Kyle J., Bolme, Cindy A., Sandberg, Richard L., & Nelson, Keith A. Machine learning to analyze images of shocked materials for precise and accurate measurements. United States. https://doi.org/10.1063/1.4998959
Dresselhaus-Cooper, Leora, Howard, Marylesa, Hock, Margaret C., Meehan, B. T., Ramos, Kyle J., Bolme, Cindy A., Sandberg, Richard L., and Nelson, Keith A. Thu .
"Machine learning to analyze images of shocked materials for precise and accurate measurements". United States. https://doi.org/10.1063/1.4998959.
@article{osti_1390398,
title = {Machine learning to analyze images of shocked materials for precise and accurate measurements},
author = {Dresselhaus-Cooper, Leora and Howard, Marylesa and Hock, Margaret C. and Meehan, B. T. and Ramos, Kyle J. and Bolme, Cindy A. and Sandberg, Richard L. and Nelson, Keith A.},
abstractNote = {},
doi = {10.1063/1.4998959},
journal = {Journal of Applied Physics},
number = 10,
volume = 122,
place = {United States},
year = {2017},
month = {9}
}
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https://doi.org/10.1063/1.4998959
https://doi.org/10.1063/1.4998959
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