Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session Q32: Deep Learning Computer Vision
3:00 PM–4:12 PM,
Wednesday, March 16, 2022
Room: McCormick Place W-192B
Sponsoring
Unit:
GDS
Chair: William Ratcliff, GDS
Abstract: Q32.00003 : Unsupervised Machine Learning for Spatio-Temporal Characterization of Nanoscale Phenomena Imaged via Ultrafast Electron Microscopy*
3:24 PM–3:36 PM
Presenter:
Thomas E Gage
(Argonne National Laboratory)
Authors:
Faran Zhou
(Argonne National Laboratory)
Thomas E Gage
(Argonne National Laboratory)
Haihua Liu
(Argonne National Laboratory)
Ilke Arslan
(Argonne National Laboratory)
Haidan Wen
(Argonne National Laboratory)
Maria K Chan
(Argonne National Laboratory)
*This work was performed at the Center for Nanoscale Materials, a U.S. Department of Energy Office of Science User Facility, and supported by the U.S. Department of Energy, Office of Science, under Contract No. DE-AC02-06CH11357.
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700