Explainable Artificial Intelligence for Crowd Forecasting Using Global Ensemble Echo State Networks
Crowd monitoring is a primary function in diverse industrial domains, such as smart cities,
public transport, and public safety. Recent advancements in low-energy devices and rapid …
public transport, and public safety. Recent advancements in low-energy devices and rapid …
[PDF][PDF] PRNet: A Periodic Residual Learning Network for Crowd Flow Forecasting
Crowd flow forecasting, eg, predicting the crowds entering or leaving certain regions, is of
great importance to real-world urban applications. One of the key properties of crowd flow …
great importance to real-world urban applications. One of the key properties of crowd flow …
Predicting citywide crowd dynamics at big events: A deep learning system
Event crowd management has been a significant research topic with high social impact.
When some big events happen such as an earthquake, typhoon, and national festival, crowd …
When some big events happen such as an earthquake, typhoon, and national festival, crowd …
Periodic residual learning for crowd flow forecasting
Crowd flow forecasting, which aims to predict the crowds entering or leaving certain regions,
is a fundamental task in smart cities. One of the key properties of crowd flow data is …
is a fundamental task in smart cities. One of the key properties of crowd flow data is …
Crowd Safety Manager: Towards Data-Driven Active Decision Support for Planning and Control of Crowd Events
P Krishnakumari, S Hoogendoorn-Lanser… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper presents novel technology and methodology aimed at enhancing crowd
management in both the planning and operational phases. The approach encompasses …
management in both the planning and operational phases. The approach encompasses …
Deepurbanevent: A system for predicting citywide crowd dynamics at big events
Event crowd management has been a significant research topic with high social impact.
When some big events happen such as an earthquake, typhoon, and national festival, crowd …
When some big events happen such as an earthquake, typhoon, and national festival, crowd …
Communication efficient model-aware federated learning for visual crowd counting and density estimation in smart cities
Federated learning (FL) is an attractive paradigm where a number of users can improve their
local models via sharing trained models or model increments with a central server, while the …
local models via sharing trained models or model increments with a central server, while the …
Grouptron: Dynamic multi-scale graph convolutional networks for group-aware dense crowd trajectory forecasting
R Zhou, H Zhou, H Gao, M Tomizuka… - … on Robotics and …, 2022 - ieeexplore.ieee.org
Accurate, long-term forecasting of pedestrian trajectories in highly dynamic and interactive
scenes is a longstanding challenge. Recent advances in using data-driven approaches …
scenes is a longstanding challenge. Recent advances in using data-driven approaches …
Multisize patched spatial-temporal transformer network for short-and long-term crowd flow prediction
Y Xie, J Niu, Y Zhang, F Ren - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
The prediction of urban crowds is crucial not only to traffic management but also to studies
on the city-level social phenomena, such as energy consumption, urban growth, city …
on the city-level social phenomena, such as energy consumption, urban growth, city …
Crowd forecasting based on wifi sensors and lstm neural networks
To ensure effective management and security in large-scale public events, it is imperative for
the event organizers to be aware of potentially critical crowd densities. This article, therefore …
the event organizers to be aware of potentially critical crowd densities. This article, therefore …