Feature Relevance Explainers in Tabular Anomaly Detection

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Alternative title: Merkmal-Relevanz-Erklärer in tabellarischer Anomalie-Erkennung

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Notes: Würzburg, Universität Würzburg, Dissertation, 2024

Keyword: Maschinelles Lernen
Eindringerkennung
Kryptoanalyse
Explainable Artificial Intelligence
Anomalieerkennung

Event: Veröffentlichung

(where): Würzburg

(who): Universität Würzburg

(when): 2024

Creator: Tritscher, Julian

Contributor: Hotho, Andreas
Puppe, Frank

DOI: 10.25972/OPUS-37590

URN: urn:nbn:de:bvb:20-opus-375903

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:34 AM CEST

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Associated

Tritscher, Julian
Hotho, Andreas
Puppe, Frank
Universität Würzburg

Time of origin

2024

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Robust Metric based Anomaly Detection in Kernel Feature Space

Cumulative histogram as a feature selection technique for anomaly detection

Human pose feature enhancement for human anomaly detection and tracking

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That’s BAD: blind anomaly detection by implicit local feature clustering

Multimodal and multiscale feature fusion for weakly supervised video anomaly detection

Understanding the limitations of self-supervised learning for tabular anomaly detection

Latent feature reconstruction for unsupervised anomaly detection

Anomaly detection in the presence of irrelevant features

EOG feature relevance determination for microsleep detection

Robust Metric based Anomaly Detection in Kernel Feature Space

Cumulative histogram as a feature selection technique for anomaly detection

Human pose feature enhancement for human anomaly detection and tracking

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Tabular statements

Index

Tabular Summaries

That’s BAD: blind anomaly detection by implicit local feature clustering

Multimodal and multiscale feature fusion for weakly supervised video anomaly detection

Understanding the limitations of self-supervised learning for tabular anomaly detection

Latent feature reconstruction for unsupervised anomaly detection

Anomaly detection in the presence of irrelevant features

EOG feature relevance determination for microsleep detection

Robust Metric based Anomaly Detection in Kernel Feature Space

Cumulative histogram as a feature selection technique for anomaly detection

Human pose feature enhancement for human anomaly detection and tracking

Abschnitt

Tabular statements

Index

Tabular Summaries

That’s BAD: blind anomaly detection by implicit local feature clustering

Multimodal and multiscale feature fusion for weakly supervised video anomaly detection

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Feature Relevance Explainers in Tabular Anomaly Detection

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Associated

Time of origin

Other Objects (12)

Understanding the limitations of self-supervised learning for tabular anomaly detection

Latent feature reconstruction for unsupervised anomaly detection

Anomaly detection in the presence of irrelevant features

EOG feature relevance determination for microsleep detection

EOG feature relevance determination for microsleep detection

Robust Metric based Anomaly Detection in Kernel Feature Space

Cumulative histogram as a feature selection technique for anomaly detection

Human pose feature enhancement for human anomaly detection and tracking

Tabular statements

Tabular Summaries

That’s BAD: blind anomaly detection by implicit local feature clustering

Multimodal and multiscale feature fusion for weakly supervised video anomaly detection

Understanding the limitations of self-supervised learning for tabular anomaly detection

Latent feature reconstruction for unsupervised anomaly detection

Anomaly detection in the presence of irrelevant features

EOG feature relevance determination for microsleep detection

EOG feature relevance determination for microsleep detection

Robust Metric based Anomaly Detection in Kernel Feature Space

Cumulative histogram as a feature selection technique for anomaly detection

Human pose feature enhancement for human anomaly detection and tracking

Tabular statements

Tabular Summaries

That’s BAD: blind anomaly detection by implicit local feature clustering

Multimodal and multiscale feature fusion for weakly supervised video anomaly detection

Understanding the limitations of self-supervised learning for tabular anomaly detection

Latent feature reconstruction for unsupervised anomaly detection

Anomaly detection in the presence of irrelevant features

EOG feature relevance determination for microsleep detection

EOG feature relevance determination for microsleep detection

Robust Metric based Anomaly Detection in Kernel Feature Space

Cumulative histogram as a feature selection technique for anomaly detection

Human pose feature enhancement for human anomaly detection and tracking

Tabular statements

Tabular Summaries

That’s BAD: blind anomaly detection by implicit local feature clustering

Multimodal and multiscale feature fusion for weakly supervised video anomaly detection

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