Unsupervised Multi-sensor Anomaly Localization with Explainable AI

Mina Ameli; Viktor Pfanschilling; Anar Amirli; Wolfgang Maaß; Kristian Kersting

doi:10.1007/978-3-031-08333-4_41

ScienceGate Book Chapters

BOOK-CHAPTER

Unsupervised Multi-sensor Anomaly Localization with Explainable AI

Mina Ameli Viktor Pfanschilling Anar Amirli Wolfgang Maaß Kristian Kersting

Year: 2022 IFIP advances in information and communication technology Pages: 507-519 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-08333-4_41

Get Full-Text PDF Get Analytical Report

Keywords:

Anomaly detection Anomaly (physics) Computer science Artificial intelligence Multivariate statistics Data mining Pattern recognition (psychology) Machine learning

Metrics

Cited By

2.55

FWCI (Field Weighted Citation Impact)

Refs

0.90

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Explainable Artificial Intelligence (XAI)

Physical Sciences → Computer Science → Artificial Intelligence

Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Unsupervised Multi-sensor Anomaly Localization with Explainable AI

Metrics

Citation History

Topics

Related Documents

Explainable Unsupervised Multi-Sensor Industrial Anomaly Detection and Categorization

Multi-scale Feature Imitation for Unsupervised Anomaly Localization

Diffusion for Explainable Unsupervised Anomaly Detection

EVAL: Explainable Video Anomaly Localization

Unsupervised Anomaly Localization with Structural Feature-Autoencoders