Search Results for author: Jeong-Hyeon Moon

Found 2 papers, 1 papers with code

Decomposing Texture and Semantics for Out-of-distribution Detection

no code implementations29 Sep 2021 Jeong-Hyeon Moon, Namhyuk Ahn, Kyung-Ah Sohn

Out-of-distribution (OOD) detection has made significant progress in recent years because the distribution mismatch between the training and testing can severely deteriorate the reliability of a machine learning system. Nevertheless, the lack of precise interpretation of the in-distribution limits the application of OOD detection methods to real-world system pipielines.

OOD Detection Out-of-Distribution Detection

What is Wrong with One-Class Anomaly Detection?

1 code implementation20 Apr 2021 JuneKyu Park, Jeong-Hyeon Moon, Namhyuk Ahn, Kyung-Ah Sohn

From a safety perspective, a machine learning method embedded in real-world applications is required to distinguish irregular situations.

Anomaly Detection

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