Targeted Collapse Regularized Autoencoder for Anomaly Detection: Black Hole at the Center

Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the autoencoder on normal training data, anomalous inputs will exhibit a significant reconstruction error. Consequently, this...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2024-10, Vol.PP, p.1-11
Hauptverfasser:	Ghafourian, Amin, Shui, Huanyi, Upadhyay, Devesh, Gupta, Rajesh, Filev, Dimitar, Soltani, Iman
Format:	Artikel
Sprache:	eng
Schlagworte:	Anomaly detection learning dynamics regularized autoencoders representation learning
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!