March 4, 2024, 5:45 a.m. | Yuting Li, Yingyi Chen, Xuanlong Yu, Dexiong Chen, Xi Shen

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.00543v1 Announce Type: new
Abstract: In this paper, we revisit techniques for uncertainty estimation within deep neural networks and consolidate a suite of techniques to enhance their reliability. Our investigation reveals that an integrated application of diverse techniques--spanning model regularization, classifier and optimization--substantially improves the accuracy of uncertainty predictions in image classification tasks. The synergistic effect of these techniques culminates in our novel SURE approach. We rigorously evaluate SURE against the benchmark of failure prediction, a critical testbed for uncertainty …

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