Robustness
Publications
Robustness and exploration of variational and machine learning approaches to inverse problems: An overview
Alexander Auras*, Kanchana Vaishnavi Gandikota*, Hannah Droege, Michael Moeller
Published in Wiley GAMM-Mitteilungen, 2024
[pdf] [arxiv] [bibtex]
On the unreasonable vulnerability of transformers for image restoration–and an easy fix
Shashank Agnihotri, Kanchana Vaishnavi Gandikota, Julia Grabinski, Paramanand Chandramouli, Margret Keuper
Published in ICCV 2023 Workshop on Adversarial Robustness In the Real World, 2023
[pdf] [bibtex]
Evaluating Adversarial Robustness of Low dose CT Recovery
Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Hannah Droege, Michael Moeller
Published in Medical Imaging with Deep Learning (MIDL), 2023
[pdf] [bibtex]
On Adversarial Robustness of Deep Image Deblurring
Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Michael Moeller
Published in IEEE International Conference on Image Processing (ICIP), 2022
[arxiv] [bibtex]
A Simple Strategy to Provable Invariance via Orbit Mapping
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czapliński, Michael Moeller
Published in Asian Conference on Computer Vision (ACCV), 2022
[pdf] [arxiv] [bibtex]
A Simple Domain Shifting Network for Generating Low Quality Images
Guruprasad Hegde*, Avinash Nittur Ramesh*, Kanchana Vaishnavi Gandikota*,Roman Obermaisser, Michael Moeller
Published in IEEE International Conference on Pattern Recognition, 2020
[bibtex]
Current Work
Robustness of CT reconstruction
Improving robustness of histopathological image classification