Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yingfu Xu"'
Autor:
Yingfu Xu, Kevin Shidqi, Gert-Jan van Schaik, Refik Bilgic, Alexandra Dobrita, Shenqi Wang, Roy Meijer, Prithvish Nembhani, Cina Arjmand, Pietro Martinello, Anteneh Gebregiorgis, Said Hamdioui, Paul Detterer, Stefano Traferro, Mario Konijnenburg, Kanishkan Vadivel, Manolis Sifalakis, Guangzhi Tang, Amirreza Yousefzadeh
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Neuromorphic processors promise low-latency and energy-efficient processing by adopting novel brain-inspired design methodologies. Yet, current neuromorphic solutions still struggle to rival conventional deep learning accelerators' performance and ar
Externí odkaz:
https://doaj.org/article/b9216b9001bd425a90e3fae1a6231a5b
Autor:
Guangzhi Tang, Kanishkan Vadivel, Yingfu Xu, Refik Bilgic, Kevin Shidqi, Paul Detterer, Stefano Traferro, Mario Konijnenburg, Manolis Sifalakis, Gert-Jan van Schaik, Amirreza Yousefzadeh
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
Neuromorphic processors aim to emulate the biological principles of the brain to achieve high efficiency with low power consumption. However, the lack of flexibility in most neuromorphic architecture designs results in significant performance loss an
Externí odkaz:
https://doaj.org/article/7fa59a1948cb4dc8abe50ed8ab5f00a5
Autor:
Tang, Guangzhi, Vadivel, Kanishkan, Yingfu Xu, Bilgic, Refik, Shidqi, Kevin, Detterer, Paul, Traferro, Stefano, Konijnenburg, Mario, Sifalakis, Manolis, van Schaik, Gert-Jan, Yousefzadeh, Amirreza
Publikováno v:
Frontiers in Neuroscience; 2023, p01-20, 20p
Autor:
Yingfu Xu, Guido C. H. E. de Croon
Publikováno v:
ICRA
In the field of visual ego-motion estimation for Micro Air Vehicles (MAVs), fast maneuvers stay challenging mainly because of the big visual disparity and motion blur. In the pursuit of higher robustness, we study convolutional neural networks (CNNs)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd383a8ff7fe2f05a907a6660165a262
https://doi.org/10.1109/icra48506.2021.9561714
https://doi.org/10.1109/icra48506.2021.9561714
Publikováno v:
ICIA
In this paper, we propose a novel DQN-based global path planning method which enables a mobile robot to efficiently obtain its optimal path in a dense environment. The method can be broken into three steps. Firstly, we need to design and train a DQN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::390550d2df0b47f9ed63c886fa2310a4
https://doi.org/10.1109/icinfa.2018.8812452
https://doi.org/10.1109/icinfa.2018.8812452
Publikováno v:
2017 36th Chinese Control Conference (CCC).
A novel switchable multiple-mode sensor fusion algorithm for attitude estimation of quadrotor is proposed in this paper. It is a robust algorithm which shows good performance in flight conditions where sustained translational acceleration and wind di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8265803ad5cf73c32ccd1bd793b7a93d
https://doi.org/10.23919/chicc.2017.8028342
https://doi.org/10.23919/chicc.2017.8028342