Unsupervised Anomaly Detection and Localization with Generative Adversarial Networks
Konferenz: ECOC 2024 - 50th European Conference on Optical Communication
22.09.2024-26.09.2024 in Frankfurt, Germany
Tagungsband: ITG-Fb. 317: ECOC 2024
Seiten: 4Sprache: EnglischTyp: PDF
Autoren:
Abdelli, Khouloud; Lonardi, Matteo; Gripp, Jurgen; Olsson, Samuel; Boitier, Fabien; Layec, Patricia
Inhalt:
We propose a novel unsupervised anomaly detection approach using generative adversarial networks and SOP-derived spectrograms. Demonstrating remarkable efficacy, our method achieves over 97% accuracy on SOP datasets from both submarine and terrestrial fiber links, all achieved without the need for labelled data.