Cargando…
A Real-Time Vehicle Detection System under Various Bad Weather Conditions Based on a Deep Learning Model without Retraining
Numerous vehicle detection methods have been proposed to obtain trustworthy traffic data for the development of intelligent traffic systems. Most of these methods perform sufficiently well under common scenarios, such as sunny or cloudy days; however, the detection accuracy drastically decreases und...
Autores principales: | Chen, Xiu-Zhi, Chang, Chieh-Min, Yu, Chao-Wei, Chen, Yen-Lin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7600474/ https://www.ncbi.nlm.nih.gov/pubmed/33050173 http://dx.doi.org/10.3390/s20205731 |
Ejemplares similares
-
Retrain or Not Retrain? - Efficient Pruning Methods of Deep CNN Networks
por: Pietron, Marcin, et al.
Publicado: (2020) -
Measurement of Water Level in Urban Streams under Bad Weather Conditions
por: Azevedo, Joaquim Amândio, et al.
Publicado: (2021) -
Real-time vehicle target detection in inclement weather conditions based on YOLOv4
por: Wang, Rui, et al.
Publicado: (2023) -
An Overview of Autonomous Vehicles Sensors and Their Vulnerability to Weather Conditions
por: Vargas, Jorge, et al.
Publicado: (2021) -
Deep Camera–Radar Fusion with an Attention Framework for Autonomous Vehicle Vision in Foggy Weather Conditions
por: Ogunrinde, Isaac, et al.
Publicado: (2023)