TY - GEN
T1 - Deep-learning-based computational biomedical microscopy with uncertainty quantification
AU - Tian, Lei
AU - Xue, Yujia
AU - Cheng, Shiyi
AU - Li, Yunzhe
AU - Ji, Yi
N1 - Publisher Copyright:
CLEO 2020 © OSA 2020, © 2020 The Author(s).
PY - 2020
Y1 - 2020
N2 - I will present several deep learning based computational microscopy techniques including phase microscopy and imaging oximetry. Emphasis will be put on an uncertainty quantification framework for assessing the reliability of these techniques.
AB - I will present several deep learning based computational microscopy techniques including phase microscopy and imaging oximetry. Emphasis will be put on an uncertainty quantification framework for assessing the reliability of these techniques.
UR - http://www.scopus.com/inward/record.url?scp=85095114813&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85095114813&partnerID=8YFLogxK
U2 - 10.1364/CLEO_AT.2020.AW3T.1
DO - 10.1364/CLEO_AT.2020.AW3T.1
M3 - Conference contribution
AN - SCOPUS:85095114813
SN - 9781943580767
T3 - Optics InfoBase Conference Papers
BT - CLEO
PB - Optica Publishing Group (formerly OSA)
T2 - CLEO: Applications and Technology, CLEO_AT 2020
Y2 - 10 May 2020 through 15 May 2020
ER -