7 citations · 10 across the 13 of their papers we have counts for
4 papers · 1 filter
Uncertainty-Aware Retinal Vessel Segmentation via Ensemble Distillation
Jeremiah Fadugba, Petru Manescu, Bolanle Oladejo +2
Uncertainty estimation is critical for reliable medical image segmentation, particularly in retinal vessel analysis, where accurate predictions are essential for diagnostic applica…
Prototype-Guided and Lightweight Adapters for Inherent Interpretation and Generalisation in Federated Learning
Samuel Ofosu Mensah, Kerol Djoumessi, Philipp Berens
Federated learning (FL) provides a promising paradigm for collaboratively training machine learning models across distributed data sources while maintaining privacy. Nevertheless,…
Soft-CAM: Making black box models self-explainable for medical image analysis
Kerol Djoumessi, Philipp Berens
Convolutional neural networks (CNNs) are widely used for high-stakes applications like medicine, often surpassing human performance. However, most explanation methods rely on post-…
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images
Kerol Djoumessi, Samuel Ofosu Mensah, Philipp Berens
In many medical imaging tasks, convolutional neural networks (CNNs) efficiently extract local features hierarchically. More recently, vision transformers (ViTs) have gained popular…