Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network

Open public places, such as pedestrian streets, parks, and squares, are vulnerable when the pedestrians thronged into the sidewalks. The crowd count changes dynamically over time with various external factors, such as surroundings, weekends, and peak hours, so it is essential to predict the accurate...

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Detalhes bibliográficos

Principais autores:	Menghang Liu, Luning Li, Qiang Li, Yu Bai, Cheng Hu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2021-07-01
coleção:	ISPRS International Journal of Geo-Information
Assuntos:	pedestrian flow prediction graph convolutional network (GCN) open public places model performance
Acesso em linha:	https://www.mdpi.com/2220-9964/10/7/455
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