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...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 24; no. 18; p. 5951
Main Authors:	Moskalenko, Viacheslav, Kharchenko, Vyacheslav, Semenov, Serhii
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 13.09.2024 MDPI
Subjects:	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 Access:	Get full text
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