Verifying Deep Learning-based Decisions for Facial Expression Recognition
Ines Rieger,
Rene Kollmann,
Bettina Finzel
et al.
Abstract:Neural networks with high performance can still be biased towards non-relevant features. However, reliability and robustness is especially important for high-risk fields such as clinical pain treatment. We therefore propose a verification pipeline, which consists of three steps. First, we classify facial expressions with a neural network. Next, we apply layer-wise relevance propagation to create pixel-based explanations. Finally, we quantify these visual explanations based on a bounding-box method with respect… Show more
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