3 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
Asonyu Senge Njih, Yvan Guifo Fodjo, Vianney Kengne Tchendji +2
Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical limitations: reliance on onl…
TTE-CAM: Self-Explainable Class Activation Maps for Pretrained Black-Box CNNs
Kerol Djoumessi, Philipp Berens
Convolutional neural networks (CNNs) achieve state-of-the-art performance in medical image analysis yet remain opaque, limiting adoption in high-stakes clinical settings. Existing…
Towards Interpretable Foundation Models for Retinal Fundus Images
Samuel Ofosu Mensah, Camila Roa, Kerol Djoumessi +1
Foundation models are used to extract transferable representations from large amounts of unlabeled data, typically via self-supervised learning (SSL). However, many of these models…
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…