3 papers
cs.HC2025
Towards Biomarker Discovery for Early Cerebral Palsy Detection: Evaluating Explanations Through Kinematic Perturbations
Kimji N. Pellano, Inga Strümke, Daniel Groos +3
Cerebral Palsy (CP) is a prevalent motor disability in children, for which early detection can significantly improve treatment outcomes. While skeleton-based Graph Convolutional Ne…
cs.CV2024
Evaluating Explainable AI Methods in Deep Learning Models for Early Detection of Cerebral Palsy
Kimji N. Pellano, Inga Strümke, Daniel Groos +2
Early detection of Cerebral Palsy (CP) is crucial for effective intervention and monitoring. This paper tests the reliability and applicability of Explainable AI (XAI) methods usin…
cs.LG2024
From Movements to Metrics: Evaluating Explainable AI Methods in Skeleton-Based Human Activity Recognition
Kimji N. Pellano, Inga Strümke, Espen Alexander F. Ihlen
The advancement of deep learning in human activity recognition (HAR) using 3D skeleton data is critical for applications in healthcare, security, sports, and human-computer interac…