1 citations · 1 across the 11 of their papers we have counts for
12 papers
Simple, Safe, and Overlooked: Reclaiming Sustainable Domain Generalization with Statistical Color Matching
Sebastian Doerrich, Francesco Di Salvo, Shyam Nandan Rai +2
Hardware shifts, color variations, and changing patient characteristics between development and deployment routinely break trained medical image classifiers. Existing remedies fall…
Layer Selection in VLMs for Zero-Shot OOD Detection via Multi-Resolution Entropy Estimation
Shyam Nandan Rai, Francesco Di Salvo, Sebastian Doerrich +1
Out-of-distribution (OOD) detection is crucial for safe deployment of medical AI systems, where domain shifts arise across institutions, acquisition protocols, and patient populati…
TRUE-Colon: Exposing a Consistent Transfer Asymmetry in Real-Time Polyp Detection
Sebastian Doerrich, Andreas Franz Schwab, Francesco Di Salvo +3
Computer-aided detection (CADe) systems for colonoscopy promise to reduce clinical miss rates, yet reliable real-world deployment remains elusive. This translational gap stems in p…
MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification
Sebastian Doerrich, Daniel Würtinger, Francesco Di Salvo +2
Adapting deep learning models to profound clinical heterogeneity typically relies on parameter-efficient fine-tuning (PEFT) to avoid the severe overfitting associated with full end…
Vertical Fusion: Condensing Internal Representations for Robust ViT Classification
Francesco Di Salvo, Shyam Nandan Rai, Hamed Damirchi +4
Despite exposing rich intermediate representations, Vision Transformers (ViTs) are almost exclusively utilized as black-box feature extractors, where only the last layer is conside…
Towards Safer and Understandable Driver Intention Prediction
Mukilan Karuppasamy, Shankar Gangisetty, Shyam Nandan Rai +2
Autonomous driving (AD) systems are becoming increasingly capable of handling complex tasks, mainly due to recent advances in deep learning and AI. As interactions between autonomo…