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MedMNIST-C: Comprehensive benchmark and improved classifier robustness
  by simulating realistic image corruptions
v1v2v3 (latest)

MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions

25 June 2024
Francesco Di Salvo
Sebastian Doerrich
Christian Ledig
    OOD
ArXiv (abs)PDFHTMLGithub (23★)

Papers citing "MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions"

4 / 4 papers shown
T3: Test-Time Model Merging in VLMs for Zero-Shot Medical Imaging Analysis
T3: Test-Time Model Merging in VLMs for Zero-Shot Medical Imaging Analysis
Raza Imam
Hu Wang
Dwarikanath Mahapatra
Mohammad Yaqub
MoMe
295
0
0
31 Oct 2025
Deep Feedback Models
Deep Feedback Models
David Calhas
Arlindo L. Oliveira
AI4CE
134
0
0
19 Sep 2025
On the Robustness of Medical Vision-Language Models: Are they Truly Generalizable?
On the Robustness of Medical Vision-Language Models: Are they Truly Generalizable?Annual Conference on Medical Image Understanding and Analysis (MIUA), 2025
Raza Imam
Rufael Marew
Mohammad Yaqub
AAMLVLM
339
3
0
21 May 2025
Investigating the Quality of DermaMNIST and Fitzpatrick17k Dermatological Image Datasets
Investigating the Quality of DermaMNIST and Fitzpatrick17k Dermatological Image DatasetsScientific Data (Sci Data), 2024
Kumar Abhishek
Aditi Jain
Ghassan Hamarneh
353
15
0
25 Jan 2024
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