SEMPro: A Data-Driven Pipeline To Learn Structure–Property Insights from Scanning Electron Microscopy Images
- Award ID(s):
- 2011924
- PAR ID:
- 10470572
- Publisher / Repository:
- American Chemical Society
- Date Published:
- Journal Name:
- ACS Materials Letters
- Volume:
- 5
- Issue:
- 11
- ISSN:
- 2639-4979
- Format(s):
- Medium: X Size: p. 3117-3125
- Size(s):
- p. 3117-3125
- Sponsoring Org:
- National Science Foundation
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