Power-efficient analog-to-information image sensors: The fuel of AI microsystems

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Título:	Power-efficient analog-to-information image sensors: The fuel of AI microsystems
Autor:	Rodríguez-Vázquez, Ángel CSIC ORCID; Leñero-Bardallo, J. A. CSIC ORCID
Fecha de publicación:	2022
Editor:	Taylor & Francis
Citación:	AI Knowledge Transfer from the University to Society. Applications in High-Impact Sectors (Cap. 4.7): 84-87 (2022)
Resumen:	This project explores innovative architectural concepts for image sensors with embedded intelligence. The main attributes of these architectures are the use of non-Von Neumann paradigms and the extensive usage of event-driven concepts. The goal is to achieve vision with unprecedented throughput and energy efficiency.
URI:	http://hdl.handle.net/10261/337036
ISBN:	9781003276609
Aparece en las colecciones:	(IMSE-CNM) Libros y partes de libros