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001034460 005__ 20241219210859.0
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001034460 037__ $$aFZJ-2024-07226
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001034460 1001_ $$00009-0006-9119-4139$$aAbubaker, Mohamad$$b0
001034460 245__ $$aRPEE-Heads: A Benchmark for Pedestrian Head Detection in Crowd Videos
001034460 260__ $$aJülich$$bForschungszentrum Jülich$$c2024
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001034460 520__ $$aRPEE-Heads (Railway Platforms and Event Entrances-Heads) is a new benchmark for pedestrian head detection in crowded environments. It focuses on railway platforms and event entrances, where risks frequently arise. The benchmark aims to improve pedestrian head detection at railway platforms and event entrances, helping to develop accurate deep learning models for several crowd safety applications. It includes: 1) A dataset comprising 109913 head annotations across 1886 images, with an average of approximately 56.2 annotated heads per image.  2) An empirical comparative analysis of eight state-of-the-art deep learning algorithms for head detection was conducted across several publicly available image datasets and the newly introduced RPEE-Heads dataset. 3) An empirical study on head size’s impact on detection algorithms’ performance.
001034460 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001034460 536__ $$0G:(BMBF)01DH16027$$aPilotprojekt zur Entwicklung eines palästinensisch-deutschen Forschungs- und Promotionsprogramms 'Palestinian-German Science Bridge' (01DH16027)$$c01DH16027$$x1
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001034460 7001_ $$00009-0008-2715-3345$$aAlsadder, Zubayda$$b1
001034460 7001_ $$00000-0003-4803-6689$$aAbdelhaq, Hamed$$b2
001034460 7001_ $$0P:(DE-Juel1)132064$$aBoltes, Maik$$b3
001034460 7001_ $$0P:(DE-Juel1)185971$$aAlia, Ahmed$$b4
001034460 773__ $$a10.34735/PED.2024.2
001034460 8564_ $$uhttp://ped.fz-juelich.de/da/2024rpee_heads
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001034460 9141_ $$y2024
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