no code implementations • 14 Aug 2023 • Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter Schüffler, Nassir Navab
Leveraging this, we introduce DISBELIEVE, a local model poisoning attack that creates malicious parameters or gradients such that their distance to benign clients' parameters or gradients is low respectively but at the same time their adverse effect on the global model's performance is high.
no code implementations • 5 Nov 2022 • Mane Margaryan, Matthias Seibold, Indu Joshi, Mazda Farshad, Philipp Fürnstahl, Nassir Navab
In contrast to previously proposed fully convolutional models, the proposed model implements residual Squeeze and Excitation modules in the generator architecture.
no code implementations • 19 Aug 2022 • Indu Joshi, Marcel Grimmer, Christian Rathgeb, Christoph Busch, Francois Bremond, Antitza Dantcheva
This survey is intended for researchers and practitioners in the field of human analysis.
no code implementations • 23 Dec 2021 • Mohammed Asad Karim, Indu Joshi, Pratik Mazumder, Pravendra Singh
We apply our proposed approach to state-of-the-art class-incremental learning methods and empirically show that our framework significantly improves the performance of these methods.
no code implementations • 3 Jul 2021 • Indu Joshi, Ayush Utkarsh, Riya Kothari, Vinod K Kurmi, Antitza Dantcheva, Sumantra Dutta Roy, Prem Kumar Kalra
In order to save the human effort in generating annotations required by state-of-the-art, we propose a fingerprint roi segmentation model which aligns the features of fingerprint images derived from the unseen sensor such that they are similar to the ones obtained from the fingerprints whose ground truth roi masks are available for training.
no code implementations • 2 Jul 2021 • Indu Joshi, Ayush Utkarsh, Riya Kothari, Vinod K Kurmi, Antitza Dantcheva, Sumantra Dutta Roy, Prem Kumar Kalra
The effectiveness of fingerprint-based authentication systems on good quality fingerprints is established long back.