Model and Method for Providing Resilience to Resource-Constrained AI-System

Artificial intelligence technologies are becoming increasingly prevalent in resource-constrained, safety-critical embedded systems. Numerous methods exist to enhance the resilience of AI systems against disruptive influences. However, when resources are limited, ensuring cost-effective resilience be...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 24; H. 18; S. 5951
Hauptverfasser:	Moskalenko, Viacheslav, Kharchenko, Vyacheslav, Semenov, Serhii
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 13.09.2024 MDPI
Schlagworte:	Adaptation adversarial attack affordable resilience Artificial intelligence Business metrics Comparative analysis concept drift dynamic deep neural networks Edge computing Efficiency Embedded systems fault injection Fault tolerance Methods Neural networks R&D Research & development robustness Ukraine adversarial attack robustness dynamic deep neural networks affordable resilience fault injection concept drift
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!