A Aralex Aachen research explorer

January 01, 2020 article Open access

Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder

DOI: 10.1109/access.2020.2977892 Full text (OA) OpenAlex

Authors 0

Author list not loaded yet.

Cited by 4 stored of 175

PATH: A discrete-sequence dataset for evaluating online unsupervised anomaly detection approaches for multivariate time series
2025 Big Data Research article Computer Science Anomaly Detection Techniques and Applications Open access

1

citations
TeVAE: A Variational Autoencoder Approach for Discrete Online Anomaly Detection in Variable-State Multivariate Time-Series Data
2025 Studies in computational intelligence conference-paper Computer Science Anomaly Detection Techniques and Applications Open access

2

citations
MA-VAE: Multi-Head Attention-Based Variational Autoencoder Approach for Anomaly Detection in Multivariate Time-Series Applied to Automotive Endurance Powertrain Testing
2023 International Joint Conference on Computational Intelligence conference-paper Computer Science Anomaly Detection Techniques and Applications Open access

9

citations
Online Time-series Anomaly Detection: A Survey of Modern Model-based Approaches
2022 Research Square preprint Computer Science Anomaly Detection Techniques and Applications Open access

5

citations

4 results

References 0