Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection

This paper presents a fast, principled approach for detecting anomalous and out-of-distribution (OOD) samples in deep neural networks (DNN). We propose the application of linear statistical dimensionality reduction techniques on the semantic features produced by a DNN, in order to capture the low-di...

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Bibliographic Details
Main Authors Ndiour, Ibrahima J, Ahuja, Nilesh A, Tickoo, Omesh
Format Journal Article
LanguageEnglish
Published 19.03.2022
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