Channel spatio-temporal convolutional network for pedestrian trajectory prediction-Reference-Cited by-同舟云学术

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Channel spatio-temporal convolutional network for pedestrian trajectory prediction

Published:2024-06-20 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Lu Zhonghao,Luo Yonglong,Xu Lina,Hu Ying,Zheng Xiaoyao,Sun Liping

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

the University Collaborative Innovation Project of Anhui Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13042-024-02245-w.pdf

Reference50 articles.

1. Golchoubian M, Ghafurian M, Dautenhahn K et al (2023) Pedestrian trajectory prediction in pedestrian-vehicle mixed environments: a systematic review. IEEE Trans Intell Transp Syst 24:11544–11567

2. Li Z, Chen Z, Li Y et al (2024) Context-aware trajectory prediction for autonomous driving in heterogeneous environments. Compu Aided Civ Infrastruct Eng 39(1):120–135

3. Peng H, Zhang J, Huang X, Hao Z, Li A, Yu Z, Yu PS (2024) Unsupervised social bot detection via structural information theory. ACM Trans Inf Syst. https://doi.org/10.1145/3660522

4. Zhang X, Yang X, Zhang W et al (2021) Crowd emotion evaluation based on fuzzy inference of arousal and valence. Neurocomputing 445:194–205

5. Rudenko A, Palmieri L, Herman M, Kitani KM, Gavrila DM, Arras KO (2020) Human motion trajectory prediction: a survey. Int J Robot Res 39(8):895–935

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