Deep Evidential Uncertainty Estimation for Semantic Segmentation under Out-Of-Distribution Obstacles
Abstract: In order to navigate safely and reliably in novel environments, robots must estimate perceptual uncertainty when confronted with out-of-distribution (OOD) obstacles not seen in training data ...
Abstract: The present work concerns side-channel attacks on cryptographic devices protected with the advanced encryption standard (AES). In this regard, the assessment of guessing entropy (GE) and the ...
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