Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Yeping Hu"'
Autor:
Yeping Hu, Bo Lei, Yash Girish Shah, Jose Cadena, Amar Saini, Grigorios Panagakos, Phan Nguyen
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the
Externí odkaz:
https://doaj.org/article/33c8bed172314ef5b2586469ffe3b9a9
Autor:
Yeping, Hu, author
Publikováno v:
Globalisation – Cultures – Religions / Globalisierung – Kulturen – Religionen. :297-308
Publikováno v:
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Trajectory prediction is one of the essential tasks for autonomous vehicles. Recent progress in machine learning gave birth to a series of advanced trajectory prediction algorithms. Lately, the effectiveness of using graph neural networks (GNNs) with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8209b8bf4e595b6e14b06bee74e07f95
https://doi.org/10.1109/iros47612.2022.9981096
https://doi.org/10.1109/iros47612.2022.9981096
Autor:
YEPING, HU
Publikováno v:
World Affairs: The Journal of International Issues, 2004 Oct 01. 8(4), 74-87.
Externí odkaz:
https://www.jstor.org/stable/48504908
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
In today’s era of increasing energy constraints, harnessing the power of electromagnetic waves and converting them into directly usable energy has great potential in the field of renewable energy. This paper presents a highly efficient electromagne
Externí odkaz:
https://doaj.org/article/52ad36209b634296871e4458ca860fef
Accurately predicting the possible behaviors of traffic participants is an essential capability for autonomous vehicles. Since autonomous vehicles need to navigate in dynamically changing environments, they are expected to make accurate predictions r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d658b199c29b27015ab3460dadb661d
Publikováno v:
ITSC
Accurately predicting future behaviors of surrounding vehicles is an essential capability for autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others, however, are full of uncertainties. Both rational and irration
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ab3a2a08231ea87b873acc943893d9d
https://doi.org/10.1109/itsc.2019.8917105
https://doi.org/10.1109/itsc.2019.8917105
Accurately tracking and predicting behaviors of surrounding objects are key prerequisites for intelligent systems such as autonomous vehicles to achieve safe and high-quality decision making and motion planning. However, there still remain challenges
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfe48cc9e9e2290d574b7d27f0984def
http://arxiv.org/abs/1908.09031
http://arxiv.org/abs/1908.09031
Publikováno v:
ITSC
Understanding human driving behavior is important for autonomous vehicles. In this paper, we propose an interpretable human behavior model in interactive driving scenarios based on the cumulative prospect theory (CPT). As a non-expected utility theor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eaf38d3661a5522d1678b4c4253d8ad1
http://arxiv.org/abs/1907.08707
http://arxiv.org/abs/1907.08707
Publikováno v:
2019 IEEE Intelligent Vehicles Symposium (IV).
For autonomous agents to successfully operate in real world, the ability to anticipate future motions of surrounding entities in the scene can greatly enhance their safety levels since potentially dangerous situations could be avoided in advance. Whi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5014d870a28f584a637dafb2be896e7a
https://doi.org/10.1109/ivs.2019.8813796
https://doi.org/10.1109/ivs.2019.8813796