Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles

Jorge E. Espinosa; Jairo Espinosa; Sergio A. Velastin

doi:10.1007/978-3-031-08859-9_6

Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles

Jorge E. Espinosa, Jairo Espinosa, Sergio A. Velastin

Resultado de la investigación: Contribución a los tipos de informe/libro › Capítulo

Idioma original	Inglés
Título de la publicación alojada	Advances in Science, Technology and Innovation
Editorial	Springer Nature
Páginas	59-73
Número de páginas	15
DOI	https://doi.org/10.1007/978-3-031-08859-9_6
Estado	Publicada - 2022
Publicado de forma externa	Sí

Serie de la publicación

Nombre	Advances in Science, Technology and Innovation
ISSN (versión impresa)	2522-8714
ISSN (versión digital)	2522-8722

Nota bibliográfica

Funding Information:
Acknowledgements This work was partially supported by COL-CIENCIAS project: Reduccion de Emisiones Vehiculares Mediante el Modelado y Gestion Optima de Trafico en Areas Metropolitanas— Caso Medellin—Area Metropolitana del Valle de Aburra, codigo 111874558167, CT 049-2017. Universidad Nacional de Colombia. Proyecto HERMES 25374. The authors gratefully acknowledge the support of NVIDIA Corporation with the donation of GPUs used for this research. Specially thanks to Eng. MSc. Jose Arroyo on whose Master's thesis this work was largely based.

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

!!!ASJC Scopus Subject Areas

Arquitectura
Química ambiental
Energías renovables, sostenibilidad y medio ambiente

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keywords = "CNN, Deep learning, Faster R-CNN, Multiple object tracking, Region-based detector, Urban vehicle detection, Urban vehicle tracking, Yolo",

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Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles

Serie de la publicación

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!!!ASJC Scopus Subject Areas

ODS de las Naciones Unidas

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