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Between Generating Noise and Generating Images: Noise in the Correct
  Frequency Improves the Quality of Synthetic Histopathology Images for Digital
  Pathology

Between Generating Noise and Generating Images: Noise in the Correct Frequency Improves the Quality of Synthetic Histopathology Images for Digital Pathology

13 February 2023
Nati Daniel
Eliel Aknin
Ariel Larey
Yoni Peretz
G. Sela
Y. Fisher
Y. Savir
    MedIm
ArXivPDFHTML

Papers citing "Between Generating Noise and Generating Images: Noise in the Correct Frequency Improves the Quality of Synthetic Histopathology Images for Digital Pathology"

3 / 3 papers shown
Title
Generating synthetic multi-dimensional molecular-mediator time series
  data for artificial intelligence-based disease trajectory forecasting and
  drug development digital twins: Considerations
Generating synthetic multi-dimensional molecular-mediator time series data for artificial intelligence-based disease trajectory forecasting and drug development digital twins: Considerations
G. An
Chase Cockrell
28
2
0
16 Mar 2023
Machine learning approach for biopsy-based identification of
  eosinophilic esophagitis reveals importance of global features
Machine learning approach for biopsy-based identification of eosinophilic esophagitis reveals importance of global features
Tomer Czyzewski
Nati Daniel
M. Rochman
J. Caldwell
Garrett A. Osswald
M. Collins
M. Rothenberg
Y. Savir
27
22
0
13 Jan 2021
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
212
19,494
0
21 Nov 2016
1