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Results of 'iCaveats', a Project on the Integration of Architectures and Components for Embedded Vision

Authors: Ricardo Carmona-Galán; Jorge Fernández-Berni; Ángel Rodríguez-Vázquez; Paula López Martinez 0001; Víctor Manuel Brea Sánchez; Diego Cabello Ferrer; Ginés Doménech-Asensi; +2 Authors

Results of 'iCaveats', a Project on the Integration of Architectures and Components for Embedded Vision

Abstract

iCaveats is a Project on the integration of components and architectures for embedded vision in transport and security applications. A compact and efficient implementation of autonomous vision systems is difficult to be accomplished by using the conventional image processing chain. In this project we have targeted alternative approaches, that exploit the inherent parallelism in the visual stimulus, and hierarchical multilevel optimization. A set of demos showcase the advances at sensor level, in adapted architectures for signal processing and in power management and energy harvesting.

Proceeding: ICDSC '18 Proceedings of the 12th International Conference on Distributed Smart Cameras Article No. 24 Eindhoven, Netherlands — September 03 - 04, 2018

Peer reviewed

Country
Spain
Keywords

Smart image sensors, Vision chips, Embedded vision systems, Parallel concurrent processing

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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