3 citations · 7 across the 8 of their papers we have counts for
4 papers · 1 filter
LD-ViCE: Latent Diffusion Model for Video Counterfactual Explanations
Payal Varshney, Adriano Lucieri, Christoph Balada +2
Video-based AI systems are increasingly adopted in safety-critical domains such as autonomous driving and healthcare. However, interpreting their decisions remains challenging due…
Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
Payal Varshney, Adriano Lucieri, Christoph Balada +2
Concept-based explanations have emerged as an effective approach within Explainable Artificial Intelligence, enabling interpretable insights by aligning model decisions with human-…
Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage
Christoph Balada, Aida Romano-Martinez, Vincent ten Cate +9
In this study, hypertension is utilized as an indicator of individual vascular damage. This damage can be identified through machine learning techniques, providing an early risk ma…
Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification
Adriano Lucieri, Fabian Schmeisser, Christoph Peter Balada +3
It is generally believed that the human visual system is biased towards the recognition of shapes rather than textures. This assumption has led to a growing body of work aiming to…