- Weitere Titel
-
Merkmal-Relevanz-Erklärer in tabellarischer Anomalie-Erkennung
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Würzburg, Universität Würzburg, Dissertation, 2024
- Schlagwort
-
Maschinelles Lernen
Eindringerkennung
Kryptoanalyse
Explainable Artificial Intelligence
Anomalieerkennung
- Ereignis
-
Veröffentlichung
- (wo)
-
Würzburg
- (wer)
-
Universität Würzburg
- (wann)
-
2024
- Urheber
-
Tritscher, Julian
- Beteiligte Personen und Organisationen
-
Hotho, Andreas
Puppe, Frank
- DOI
-
10.25972/OPUS-37590
- URN
-
urn:nbn:de:bvb:20-opus-375903
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:34 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Tritscher, Julian
- Hotho, Andreas
- Puppe, Frank
- Universität Würzburg
Entstanden
- 2024
Ähnliche Objekte (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