Addressing Anomaly Detection and Concept Drift in Non-Stationary IoT Environments with an Uncertainty-Aware Deep Generative Model

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Addressing Anomaly Detection and Concept Drift in Non-Stationary IoT Environments with an Uncertainty-Aware Deep Generative Model
Συγγραφείς: Mohamed, Noor El-Deen M., Awdalla, Medhat, Ali, Hossam I., Soliman, Ahmed
Πηγή: 2025 13th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Electronics, Communications, and Computations (JAC-ECC), 2025 13th International Japan-Africa Conference on. :331-336 Dec, 2025
Relation: 2025 13th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)
Βάση Δεδομένων: IEEE Xplore Digital Library
Περιγραφή
ISBN:9798331591076
9798331591083
ISSN:26903385
23764112
DOI:10.1109/JAC-ECC67970.2025.11417606