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SIFT-SNN para la seguridad de la infraestructura de flujo de tráfico: un marco de detección de anomalías consciente

Munish Rathee1, Boris Bačić1, Maryam Doborjeh1,2

  • 1School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.

Journal of imaging
|February 26, 2026
PubMed
Resumen

No abstract available in PubMed .

Palabras clave:
extracción de características SIFTdetección de anomalías en infraestructurassistemas de visión conscientes del contextodespliegue de IA en el bordesistemas de transporte inteligentesclasificación de defectos multiclasecomputación neuromórficamonitorización estructural en tiempo realanálisis de imágenes espaciotemporalesredes neuronales de espigas

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