Zobrazeno 1 - 10
of 284
pro vyhledávání: '"Zhou, Liguo"'
In order to simplify the muon detection system, this paper proposes a high-precision time measurement method based on phase-fitting by using the digitized muon pulses which are often used to extract the energy information of muons. Thus, the time and
Externí odkaz:
http://arxiv.org/abs/2411.08408
In the rapidly evolving field of autonomous driving systems, the refinement of path planning algorithms is paramount for navigating vehicles through dynamic environments, particularly in complex urban scenarios. Traditional path planning algorithms,
Externí odkaz:
http://arxiv.org/abs/2404.05423
The implementation of Autonomous Driving (AD) technologies within urban environments presents significant challenges. These challenges necessitate the development of advanced perception systems and motion planning algorithms capable of managing situa
Externí odkaz:
http://arxiv.org/abs/2402.14933
Autor:
Zhou, Liguo, Song, Yinglei, Gao, Yichao, Yu, Zhou, Sodamin, Michael, Liu, Hongshen, Ma, Liang, Liu, Lian, Liu, Hao, Liu, Yang, Li, Haichuan, Chen, Guang, Knoll, Alois
Conducting real road testing for autonomous driving algorithms can be expensive and sometimes impractical, particularly for small startups and research institutes. Thus, simulation becomes an important method for evaluating these algorithms. However,
Externí odkaz:
http://arxiv.org/abs/2401.15803
Vehicle perception systems strive to achieve comprehensive and rapid visual interpretation of their surroundings for improved safety and navigation. We introduce YOLO-BEV, an efficient framework that harnesses a unique surrounding cameras setup to ge
Externí odkaz:
http://arxiv.org/abs/2310.17379
Autor:
Liu, Lian, Zhou, liguo
CNN-based face detection methods have achieved significant progress in recent years. In addition to the strong representation ability of CNN, post-processing methods are also very important for the performance of face detection. In general, the face
Externí odkaz:
http://arxiv.org/abs/2305.10593
Several autonomous driving strategies have been applied to autonomous vehicles, especially in the collision avoidance area. The purpose of collision avoidance is achieved by adjusting the trajectory of autonomous vehicles (AV) to avoid intersection o
Externí odkaz:
http://arxiv.org/abs/2303.07352
Autonomous driving has been an active area of research and development, with various strategies being explored for decision-making in autonomous vehicles. Rule-based systems, decision trees, Markov decision processes, and Bayesian networks have been
Externí odkaz:
http://arxiv.org/abs/2303.06714
Using real road testing to optimize autonomous driving algorithms is time-consuming and capital-intensive. To solve this problem, we propose a GAN-based model that is capable of generating high-quality images across different domains. We further leve
Externí odkaz:
http://arxiv.org/abs/2302.12052
There are many artificial intelligence algorithms for autonomous driving, but directly installing these algorithms on vehicles is unrealistic and expensive. At the same time, many of these algorithms need an environment to train and optimize. Simulat
Externí odkaz:
http://arxiv.org/abs/2301.00089