Two-step Deep Learning for Computational Imaging

Autor: Guohai Situ, Ruibo Shang, Geoffrey P. Luke, Fei Wang, Kevin Hoffer-Hawlik
Rok vydání: 2021
Předmět:
Zdroj: OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP).
DOI: 10.1364/cosi.2021.cm6b.5
Popis: A two-step deep learning approach is proposed for computational imaging. This approach is robust to image model mismatches since physics priors are not needed and mitigates over-parameterization by training the network in 2 steps.
Databáze: OpenAIRE