Selection of XAI Methods Matters: Evaluation of Feature Attribution Methods for Oculomotoric Biometric Identification

Abstract

Substantial advances in oculomotoric biometric identification have been made due to deep neural networks processing non-aggregated time series data that replace methods processing theoretically motivated engineered features. However, interpretability of deep neural networks is not trivial and needs to be thoroughly investigated for future eye tracking applications. Especially in medical or legal applications explanations can be required to be provided alongside predictions. In this work, we apply several attribution methods to a state Show more