A moving track data-based method for gathering behavior prediction at early stage-Reference-Cited by-同舟云学术

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A moving track data-based method for gathering behavior prediction at early stage

Published:2021-04-07 Issue:11 Volume:51 Page:8498-8518
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Wang Sainan,Liu Yang,Wang Jing,Gao Suixiang,Yang Wenguo^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-021-02244-2.pdf

Reference23 articles.

1. Abdelghany A, Abdelghany K, Mahmassani H, Alhalabi W (2014) Modeling framework for optimal evacuation of large-scale crowded pedestrian facilities. Eur J Oper Res 237(3):1105–1118

2. Bakar N A A, Majid M A, Adam K, Allegra M (2018) Social force as a microscopic simulation model for pedestrian behavior in crowd evacuation. Adv Sci Lett

3. Liao C, Zhu K, Guo H, Tang J (2019) Simulation research on safe flow rate of bidirectional crowds using bayesian-nash equilibrium. Complexity 2019:1–15

4. Ke Y, Sukthankar R, Hebert M (2007) Event detection in crowded videos. In: IEEE International Conference on Computer Vision

5. Amit A, Ehud R, Ilan S, Daviv R (2008) Robust real-time unusual event detection using multiple fixed-location monitors. IEEE Trans Pattern Anal Mach Intell 30(3):555

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1. Human Activity Recognition Using Deep Learning : A Survey;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2023-06-10

2. A Review of Deep Learning-based Human Activity Recognition on Benchmark Video Datasets;Applied Artificial Intelligence;2022-07-11

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