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Title: End-to-End Optimized Adversarial Deep Compressed Super-Resolution Imaging via Pattern Scanning
We propose an end-to-end optimized adversarial deep compressed imaging modality. This method exploits the adversarial duality of the sensing basis and sparse representation basis in compressed sensing framework and shows solid super-resolution results.
Authors:
; ;
Award ID(s):
1847141
Publication Date:
NSF-PAR ID:
10335272
Journal Name:
OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
Page Range or eLocation-ID:
CM2E.6
Sponsoring Org:
National Science Foundation
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