Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Luyao Du"'
Publikováno v:
World Electric Vehicle Journal, Vol 15, Iss 8, p 369 (2024)
With the rapid advancement of autonomous driving technology, the recognition of vehicle lane-changing can provide effective environmental parameters for vehicle motion planning, decision-making and control, and has become a key task for intelligent v
Externí odkaz:
https://doaj.org/article/1d4a4313628d49f09fc32ddaf04f62e8
Publikováno v:
Sensors, Vol 24, Iss 13, p 4262 (2024)
Detecting bearing defects accurately and efficiently is critical for industrial safety and efficiency. This paper introduces Bearing-DETR, a deep learning model optimised using the Real-Time Detection Transformer (RT-DETR) architecture. Enhanced with
Externí odkaz:
https://doaj.org/article/55c515c8deef46f498c09ba12dba4570
Publikováno v:
Mathematics, Vol 12, Iss 1, p 124 (2023)
Vehicle detection is crucial for traffic surveillance and assisted driving. To overcome the loss of efficiency, accuracy, and stability in low-light conditions, we propose a lightweight “You Only Look Once” (YOLO) detection model. A polarized sel
Externí odkaz:
https://doaj.org/article/25db4d94c7ca40d68cedca34e89dc302
Publikováno v:
Journal of Advanced Transportation, Vol 2022 (2022)
Mixed traffic is a common phenomenon in urban environment. For the mixed traffic situation, the detection of traffic obstacles, including motor vehicle, non-motor vehicle, and pedestrian, is an essential task for intelligent and connected vehicles (I
Externí odkaz:
https://doaj.org/article/9af9c9df708c4406a3338d9bba0c9613
Publikováno v:
Machines, Vol 10, Iss 8, p 626 (2022)
Vehicle taillight intention detection is an important application for perception and decision making by intelligent vehicles. However, effectively improving detection precision with sufficient real-time performance is a critical issue in practical ap
Externí odkaz:
https://doaj.org/article/2f83ee8e087d4daeb267317ff990fa48
Publikováno v:
Machines, Vol 9, Iss 10, p 215 (2021)
In order to improve vehicle control safety in intelligent and connected environments, a fuzzy drive control strategy is proposed. Through the fusion of vehicle driving data, an early warning level model was established, and the fuzzy control method w
Externí odkaz:
https://doaj.org/article/0cfbbe7fd67c435a80e85499974088a8
Publikováno v:
Sensors, Vol 21, Iss 18, p 6092 (2021)
Beacon messages and emergency messages in vehicular ad hoc networks (VANETs) require a lower delay and higher reliability. The optimal MAC protocol can effectively reduce data collision in VANETs communication, thus minimizing delay and improving rel
Externí odkaz:
https://doaj.org/article/39d187e3b5464df491d30567ab39d9be
Publikováno v:
Sensors, Vol 20, Iss 21, p 6162 (2020)
To improve the standard point positioning (SPP) accuracy of integrated BDS (BeiDou Navigation Satellite System)/GPS (Global Positioning System) at the receiver end, a novel approach based on Long Short-Term Memory (LSTM) error correction recurrent ne
Externí odkaz:
https://doaj.org/article/9ddbe01694e8456dac33108d5ac76528
Publikováno v:
IEEE Sensors Journal. 22:12428-12443
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7b80ed4cc874a668f22e261fe58dbae
https://doi.org/10.1109/jsen.2022.3175158
https://doi.org/10.1109/jsen.2022.3175158
Publikováno v:
Computational Intelligence and Neuroscience, Vol 2022 (2022)
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience
The prediction of lane-change behavior is a challenging issue in intelligent and connected vehicles (ICVs), which can help vehicles predict in advance and change lanes safely. In this paper, a novel intelligent approach, which considering both the dr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33d0fb6213eed6cab2f2a8d8450bff5d
https://doi.org/10.1155/2022/9516218
https://doi.org/10.1155/2022/9516218