Overview of Memory-Efficient Architectures for Deep Learning in Real-Time Systems

With advancements in artificial intelligence (AI), deep learning (DL) has become crucial for real-time data analytics in areas like autonomous driving, healthcare, and predictive maintenance; however, its computational and memory demands often exceed the capabilities of low-end devices. This paper e...

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Bibliographic Details

Published in:	Engineering proceedings Vol. 104; no. 1; p. 77
Main Authors:	Bilgin Demir, Ervin Domazet, Daniela Mechkaroska
Format:	Journal Article
Language:	English
Published:	MDPI AG 01.09.2025
Subjects:	deep learning low-power devices memory-efficient architectures parameter pruning quantization real-time data processing
ISSN:	2673-4591
Online Access:	Get full text
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