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Title: Machine learning to analyze images of shocked materials for precise and accurate measurements

Authors:
ORCiD logo [1];  [2];  [2];  [2];  [3]; ORCiD logo [3];  [3];  [1]
  1. Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA, Institute for Soldier Nanotechnology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
  2. Nevada National Security Site, North Las Vegas, Nevada 89030, USA
  3. 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. 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., and Nelson, Keith A. Thu . "Machine learning to analyze images of shocked materials for precise and accurate measurements". United States. doi: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}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1063/1.4998959

Citation Metrics:
Cited by: 1 work
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