ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2001.03493
  4. Cited By
A Two-step-training Deep Learning Framework for Real-time Computational
  Imaging without Physics Priors

A Two-step-training Deep Learning Framework for Real-time Computational Imaging without Physics Priors

10 January 2020
Ruibo Shang
Kevin Hoffer-Hawlik
Geoffrey P. Luke
ArXivPDFHTML

Papers citing "A Two-step-training Deep Learning Framework for Real-time Computational Imaging without Physics Priors"

2 / 2 papers shown
Title
Deep learning for biomedical photoacoustic imaging: A review
Deep learning for biomedical photoacoustic imaging: A review
J. Gröhl
Melanie Schellenberg
Kris K. Dreher
Lena Maier-Hein
35
191
0
05 Nov 2020
Deep Learning in Photoacoustic Tomography: Current approaches and future
  directions
Deep Learning in Photoacoustic Tomography: Current approaches and future directions
A. Hauptmann
B. Cox
36
130
0
16 Sep 2020
1