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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/58675
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dc.contributor.authorTang Yi-
dc.contributor.authorGerman, O. V.-
dc.coverage.spatialМинскen_US
dc.date.accessioned2025-01-11T07:17:32Z-
dc.date.available2025-01-11T07:17:32Z-
dc.date.issued2024-
dc.identifier.citationTang Yi. А hybrid agent-centric and scene-centric approach for multi-agent trajectory prediction / Tang Yi, O. V. German // Информационные технологии и системы 2024 (ИТС 2024) = Information Technologies and Systems 2024 (ITS 2024) : материалы международной научной конференции, Минск, 20 ноября 2024 г. / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Л. Ю. Шилин [и др.]. – Минск, 2024. – С. 200–201.en_US
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/58675-
dc.description.abstractAccurately predicting the future trajectories of agents in autonomous driving is crucial for safe navigation and decision-making. Traditional trajectory prediction models have limitations when dealing with complex multi-agent interactions. In this paper, we propose a hybrid approach that leverages the strengths of both agent-centric and scene-centric models by using agent-centric normalization for dynamic agents and a scene-centric framework for static map elements.en_US
dc.language.isoenen_US
dc.publisherБГУИРen_US
dc.subjectматериалы конференцийen_US
dc.subjectautomated systemsen_US
dc.subjectmulti-agent systemsen_US
dc.subjectautonomous drivingen_US
dc.subjectmachine learningen_US
dc.titleА hybrid agent-centric and scene-centric approach for multi-agent trajectory predictionen_US
dc.typeArticleen_US
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