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Roadside video data analysis: deep learning

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning...

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Detalles Bibliográficos
Autores principales: Verma, Brijesh, Zhang, Ligang, Stockwell, David
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-10-4539-4
http://cds.cern.ch/record/2262146
Descripción
Sumario:This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.