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High-Profile VRU Detection on Resource-Constrained Hardware Using YOLOv3/v4 on BDD100K

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High-Profile VRU Detection on Resource-Constrained Hardware Using YOLOv3/v4 on BDD100K

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Ortiz, V.; Salvador Igual, I.; Del Tejo Catalá, O.; Perez-Cortes, J. (2020). High-Profile VRU Detection on Resource-Constrained Hardware Using YOLOv3/v4 on BDD100K. Journal of imaging. 6(12):1-17. https://doi.org/10.3390/jimaging6120142

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Título: High-Profile VRU Detection on Resource-Constrained Hardware Using YOLOv3/v4 on BDD100K
Autor: ORTIZ, V. Salvador Igual, Ismael Del Tejo Catalá, Omar Perez-Cortes, Juan-Carlos
Entidad UPV: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] Vulnerable Road User (VRU) detection is a major application of object detection with the aim of helping reduce accidents in advanced driver-assistance systems and enabling the development of autonomous vehicles. Due ...[+]
Palabras clave: On-road detection , Artificial intelligence , Machine learning , Convolutional neural networks , Resource-constrained hardware , One-stage detectors , Advanced driver-assistance systems , Vulnerable road users
Derechos de uso: Reconocimiento (by)
Fuente:
Journal of imaging. (eissn: 2313-433X )
DOI: 10.3390/jimaging6120142
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/jimaging6120142
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/783190/EU/Programmable Systems for Intelligence in Automobiles/
Agradecimientos:
PRYSTINE has received funding within the Electronic Components and Systems for European Leadership Joint Undertaking (ECSEL JU) in collaboration with the European Union's H2020 Framework Program and National Authorities, ...[+]
Tipo: Artículo

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Yolo v4, v3 and v2 for Windows and Linuxhttps://github.com/AlexeyAB/darknet

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