A Simple Framework for Robust Out-of-Distribution Detection
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DOI: 10.1109/access.2022.3153723
Abstract: Out-of-distribution (OOD) detection, i.e., identifying whether a given test sample is drawn from outside the training distribution, is essential for a deep classifier to be deployed in a real-world application. The existing state-of-the-art methods of… read more here.
Keywords: ood detection; simple framework; framework robust; distribution ... See more keywords
Out-of-Distribution Detection Based on Feature Fusion in Neural Network Classifier Pre-Trained by PEDCC-Loss
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3184694
Abstract: Out-of-distribution (OOD) detection is related to the security and stability of deep learning models deployed in the real world. The existing OOD detection algorithms based on the neural network normally use a single scoring function… read more here.
Keywords: neural network; detection; distribution; ood detection ... See more keywords