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An End-to-End Deep Learning Pipeline for Urban Noise Monitoring with Spatiotemporal Validation

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Dettagli Bibliografici
Autore principale:	Yalçınkaya, Mehmet Ali
Natura:	Recurso digital
Lingua:	inglese
Pubblicazione:	Zenodo 2026
Soggetti:	urban noise monitoring audio classification deep learning CNN14 SONYC-UST multi-label classification spatiotemporal analysis probability calibration TorchScript environmental sound
Accesso online:	Acceder al recurso
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