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eess.IV2024
Federated Learning for Blind Image Super-Resolution
Brian B. Moser, Ahmed Anwar, Federico Raue +2
Traditional blind image SR methods need to model real-world degradations precisely. Consequently, current research struggles with this dilemma by assuming idealized degradations, w…
eess.IV2023
Medi-CAT: Contrastive Adversarial Training for Medical Image Classification
Pervaiz Iqbal Khan, Andreas Dengel, Sheraz Ahmed
There are not many large medical image datasets available. For these datasets, too small deep learning models can't learn useful features, so they don't work well due to underfitti…