This deliverable describes the efforts done during Period 1, Period 2 and part of Period 3 in the Work Package 3 of the CrowdDNA project towards developing a new crowd simulator algorithm tailored to model both macro and micro-level crowd characteristics.
This deliverable describes the efforts done during periods 1, 2 and half-way through 3 in the Work Package 3 (WP3) of the project towards, first, generating synthetic data and, second, training a detector.
H. Lügering, A.F. Alia and A. Sieben
Dan Casas and Marc Comino-Trinidad
This report details the work completed to achieve deliverable D1.3 Field Data and outlines the data captured, analysis and sharing of data and the interrelation of this deliverable with other consortium partners and deliverables.
CrowdDNA H2020 Project‘s partners had a productive week!
Wei Xiang, Haoteng Yin, He Wang, Xiaogang Jin
Alexis Jensen, Thomas Chatagnon, Niloofar Khoshsiyar, Daniele Reda, Michiel van de Panne, Charles Pontonnier and Julien Pettré
Sina Feldmann, Juliane Adrian
Zhengzhi Lu, He Wang, Ziyi Chang, Guoan Yang, Hubert Shum
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This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 899739.