Zobrazeno 1 - 10
of 14 896
pro vyhledávání: '"A. Drews"'
Publikováno v:
Atmospheric Chemistry and Physics, Vol 22, Pp 7893-7904 (2022)
Despite several studies on decadal-scale solar influence on climate, a systematic analysis of the Sun's contribution to decadal surface climate predictability is still missing. Here, we disentangle the solar-cycle-induced climate response from intern
Externí odkaz:
https://doaj.org/article/0bdbbe5d698c4ecabf5e61ba9e8cb099
Multi-sensor fusion is crucial for accurate 3D object detection in autonomous driving, with cameras and LiDAR being the most commonly used sensors. However, existing methods perform sensor fusion in a single view by projecting features from both moda
Externí odkaz:
http://arxiv.org/abs/2410.07475
Autor:
Costa, Miguel, Petersen, Morten W., Vandervoort, Arthur, Drews, Martin, Morrissey, Karyn, Pereira, Francisco C.
Due to climate change the frequency and intensity of extreme rainfall events, which contribute to urban flooding, are expected to increase in many places. These floods can damage transport infrastructure and disrupt mobility, highlighting the need fo
Externí odkaz:
http://arxiv.org/abs/2409.18574
We represent a vehicle dynamics model for autonomous driving near the limits of handling via a multi-layer neural network. Online adaptation is desirable in order to address unseen environments. However, the model needs to adapt to new environments w
Externí odkaz:
http://arxiv.org/abs/2409.14950
Autor:
Kich, Victor Augusto, Kolling, Alisson Henrique, de Jesus, Junior Costa, Heisler, Gabriel V., Jacobs, Hiago, Bottega, Jair Augusto, Kelbouscas, André L. da S., Ohya, Akihisa, Grando, Ricardo Bedin, Drews-Jr, Paulo Lilles Jorge, Gamarra, Daniel Fernando Tello
This paper introduces novel deep reinforcement learning (Deep-RL) techniques using parallel distributional actor-critic networks for navigating terrestrial mobile robots. Our approaches use laser range findings, relative distance, and angle to the ta
Externí odkaz:
http://arxiv.org/abs/2408.05744
Polar ice develops anisotropic crystal orientation fabrics under deformation, yet ice is most often modelled as an isotropic fluid. We present three-dimensional simulations of the crystal orientation fabric of Derwael Ice Rise including the surroundi
Externí odkaz:
http://arxiv.org/abs/2408.01069
Autor:
Grando, Ricardo B., Steinmetz, Raul, Kich, Victor A., Kolling, Alisson H., Furik, Pablo M., de Jesus, Junior C., Guterres, Bruna V., Gamarra, Daniel T., Guerra, Rodrigo S., Drews-Jr, Paulo L. J.
Deep Reinforcement Learning (DRL) has emerged as a promising approach to enhancing motion control and decision-making through a wide range of robotic applications. While prior research has demonstrated the efficacy of DRL algorithms in facilitating a
Externí odkaz:
http://arxiv.org/abs/2406.01952
Autor:
K. Matthes, A. Biastoch, S. Wahl, J. Harlaß, T. Martin, T. Brücher, A. Drews, D. Ehlert, K. Getzlaff, F. Krüger, W. Rath, M. Scheinert, F. U. Schwarzkopf, T. Bayr, H. Schmidt, W. Park
Publikováno v:
Geoscientific Model Development, Vol 13, Pp 2533-2568 (2020)
A new Earth system model, the Flexible Ocean and Climate Infrastructure (FOCI), is introduced. A first version of FOCI consists of a global high-top atmosphere (European Centre Hamburg general circulation model; ECHAM6.3) and an ocean model (Nucleus
Externí odkaz:
https://doaj.org/article/5457306c34e64faa98f9ca23aebb59ae
Autor:
Gosala, Nikhil, Petek, Kürsat, Kiran, B Ravi, Yogamani, Senthil, Drews-Jr, Paulo, Burgard, Wolfram, Valada, Abhinav
Semantic Bird's Eye View (BEV) maps offer a rich representation with strong occlusion reasoning for various decision making tasks in autonomous driving. However, most BEV mapping approaches employ a fully supervised learning paradigm that relies on l
Externí odkaz:
http://arxiv.org/abs/2405.18852
Autor:
Li, Congqiao, Agapitos, Antonios, Drews, Jovin, Duarte, Javier, Fu, Dawei, Gao, Leyun, Kansal, Raghav, Kasieczka, Gregor, Moureaux, Louis, Qu, Huilin, Suarez, Cristina Mantilla, Li, Qiang
The search for heavy resonances beyond the Standard Model (BSM) is a key objective at the LHC. While the recent use of advanced deep neural networks for boosted-jet tagging significantly enhances the sensitivity of dedicated searches, it is limited t
Externí odkaz:
http://arxiv.org/abs/2405.12972