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cs.CV2024★ 27 cited
Explaining Human Activity Recognition with SHAP: Validating Insights with Perturbation and Quantitative Measures
Felix Tempel, Espen Alexander F. Ihlen, Lars Adde +1
In Human Activity Recognition (HAR), understanding the intricacy of body movements within high-risk applications is essential. This study uses SHapley Additive exPlanations (SHAP)…
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…