Book/Dissertation / PhD Thesis

FZJ-2024-04610

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Artificial Intelligence Framework for Video Analytics: Detecting Pushing in Crowds

Alia, A. (Corresponding author)FZJ*

2024
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-763-9

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Please use a persistent id in citations: doi:10.34734/FZJ-2024-04610

Abstract: In the modern era, data has become more complex, posing additional challenges to conventional data analysis methods. This is where Artificial Intelligence comes into play, specifically Deep Learning algorithms. These algorithms can analyze such data automatically, quickly, and accurately. Moreover, they can explore complex relationships between variables and identify non-linear patterns humans may not perceive. Leveraging this potential, Deep Learning has recently become pivotal in analyzing complex data, such as video data, arising from human crowds to enhance safety. Despite considerable advancements, some challenging problems in crowd dynamics still need to be solved efficiently and automatically.

Note: Dissertation, Univ. Wuppertal, 2024

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Contributing Institute(s):

1. Zivile Sicherheitsforschung (IAS-7)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2024

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