Quality In / Quality Out: Data quality more relevant than model choice in anomaly detection with the UGR'16

  1. Camacho, J.
  2. Wasielewska, K.
  3. Espinosa, P.
  4. Fuentes-García, M.
Konferenzberichte:
Proceedings of IEEE/IFIP Network Operations and Management Symposium 2023, NOMS 2023

ISBN: 9781665477161

Datum der Publikation: 2023

Art: Konferenz-Beitrag

DOI: 10.1109/NOMS56928.2023.10154333 GOOGLE SCHOLAR
Datenquelle: Scopus