TY - GEN
T1 - Deep learning, dynamic sampling and smart energy-dispersive spectroscopy
AU - Zhang, Yan
AU - Dilshan Godaliyadda, G. M.
AU - Ferrier, Nicola
AU - Gulsoy, Emine B.
AU - Bouman, Charles A.
AU - Phatak, Charudatta
N1 - Publisher Copyright:
© OSA 2017.
PY - 2017
Y1 - 2017
N2 - A convolutional neural network (CNN) classifier is trained using simulated energy-dispersive spectroscopy data. The CNN incorporated within a dynamic sampling method is to reduce radiation exposure and data acquisition time for elemental mapping.
AB - A convolutional neural network (CNN) classifier is trained using simulated energy-dispersive spectroscopy data. The CNN incorporated within a dynamic sampling method is to reduce radiation exposure and data acquisition time for elemental mapping.
UR - http://www.scopus.com/inward/record.url?scp=85035082752&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85035082752&partnerID=8YFLogxK
U2 - 10.1364/FIO.2017.FM3C.6
DO - 10.1364/FIO.2017.FM3C.6
M3 - Conference contribution
AN - SCOPUS:85035082752
T3 - Optics InfoBase Conference Papers
BT - Frontiers in Optics, FiO 2017
PB - OSA - The Optical Society
T2 - Frontiers in Optics, FiO 2017
Y2 - 18 September 2017 through 21 September 2017
ER -