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On the Robustness of Pretraining and Self-Supervision for a Deep
  Learning-based Analysis of Diabetic Retinopathy

On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy

25 June 2021
Vignesh Srinivasan
Nils Strodthoff
Jackie Ma
Alexander Binder
Klaus-Robert Muller
Wojciech Samek
    OOD
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Papers citing "On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy"

8 / 8 papers shown
Title
Learning Self-Supervised Representations for Label Efficient
  Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus Images
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus Images
Ekta Gupta
Varun Gupta
M. Chopra
Prakash Chandra Chhipa
Marcus Liwicki
19
1
0
20 Apr 2023
Dive into Self-Supervised Learning for Medical Image Analysis: Data,
  Models and Tasks
Dive into Self-Supervised Learning for Medical Image Analysis: Data, Models and Tasks
Chuyan Zhang
Yun Gu
29
0
0
25 Sep 2022
Metadata-enhanced contrastive learning from retinal optical coherence
  tomography images
Metadata-enhanced contrastive learning from retinal optical coherence tomography images
R. Holland
Oliver Leingang
Hrvoje Bogunović
Sophie Riedl
L. Fritsche
...
U. Schmidt-Erfurth
S. Sivaprasad
A. Lotery
Daniel Rueckert
M. Menten
23
9
0
04 Aug 2022
DORA: Exploring Outlier Representations in Deep Neural Networks
DORA: Exploring Outlier Representations in Deep Neural Networks
Kirill Bykov
Mayukh Deb
Dennis Grinwald
Klaus-Robert Muller
Marina M.-C. Höhne
24
12
0
09 Jun 2022
Semi-supervised machine learning model for analysis of nanowire
  morphologies from transmission electron microscopy images
Semi-supervised machine learning model for analysis of nanowire morphologies from transmission electron microscopy images
Shizhao Lu
Brian Montz
T. Emrick
A. Jayaraman
35
7
0
25 Mar 2022
On the surprising similarities between supervised and self-supervised
  models
On the surprising similarities between supervised and self-supervised models
Robert Geirhos
Kantharaju Narayanappa
Benjamin Mitzkus
Matthias Bethge
Felix Wichmann
Wieland Brendel
OOD
SSL
DRL
74
46
0
16 Oct 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
270
3,375
0
09 Mar 2020
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,238
0
24 Jun 2017
1