Real-Time Low-Cost Traffic Monitoring Based on Quantized Convolutional Neural Networks for the CNOSSOS-EU Noise Model

Accurate urban noise mapping requires granular traffic flow characterization aligned with specific acoustic models, such as CNOSSOS-EU. Existing monitoring solutions often lack the specific categorization capabilities, cost-effectiveness, or flexibility required for large-scale deployment in resourc...

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Bibliografiske detaljer

Principais autores:	Domenico Profumo, Gonzalo de León, Alessandro Monticelli, Luca Fredianelli, Gaetano Licitra
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2026-03-01
Serier:	Sensors
Fag:	real-time vehicle detection quantized convolutional neural networks CNOSSOS-EU classification edge computing traffic flow monitoring noise assessment support
Online adgang:	https://www.mdpi.com/1424-8220/26/5/1736
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