Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Yutian Pang"'
Publikováno v:
Drones, Vol 7, Iss 7, p 456 (2023)
Forest fires are one of the most serious natural disasters that threaten forest resources. The early and accurate identification of forest fires is crucial for reducing losses. Compared with satellites and sensors, unmanned aerial vehicles (UAVs) are
Externí odkaz:
https://doaj.org/article/0327bd90783641de955e3367e6e172b0
Autor:
Michael Thomas Mohen, Yuhao Wang, Yutian Pang, Stojanche Gorceski, Peter Kostiuk, Padmanabhan K. Menon, Yongming Liu
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:7310-7320
Aircraft operations in the terminal area rely heavily on voice communications between pilots and air traffic controllers. This paper proposes a novel aircraft trajectory simulation framework by guiding the trajectory simulation following the voice co
Autor:
Yutian Pang
Publikováno v:
International Journal of English Language Studies. 4:36-43
Previous research on plants in The Time Machine has shown the importance of putting these peripheral objects to the core. Studies have indicated potential associations between corpus stylistics and cognitive stylistics, but investigations of The Time
Publikováno v:
INFORMS, Indianapolis, 2022.
Neural Networks (NNs) have been widely {used in supervised learning} due to their ability to model complex nonlinear patterns, often presented in high-dimensional data such as images and text. However, traditional NNs often lack the ability for uncer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8b8d26800672aa3fd26f2a1030280e4
http://arxiv.org/abs/2210.08608
http://arxiv.org/abs/2210.08608
Publikováno v:
AIAA AVIATION 2022 Forum.
Publikováno v:
2022 Integrated Communication, Navigation and Surveillance Conference (ICNS).
Publikováno v:
Web of Science
To evaluate the robustness gain of Bayesian neural networks on image classification tasks, we perform input perturbations, and adversarial attacks to the state-of-the-art Bayesian neural networks, with a benchmark CNN model as reference. The attacks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71c0586bc1a46dac55421661d66741fe
http://arxiv.org/abs/2106.09223
http://arxiv.org/abs/2106.09223
Fracture pattern prediction with random microstructure using a physics-informed deep neural networks
Publikováno v:
Engineering Fracture Mechanics. 268:108497