Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Yoshiki NINOMIYA"'
Publikováno v:
Data in Brief, Vol 55, Iss , Pp 110722- (2024)
The dataset presented in this article is an update of the dataset provided by K. Edanami and G. Sun entitled “Medical Radar Signal Dataset for Non-Contact Respiration and Heart Rate Measurement” [1]. The new dataset includes radar signals and ref
Externí odkaz:
https://doaj.org/article/1f814a79759a4bcf95d563f5d06cbd18
Autor:
Yuki Kitsukawa, Tatsuya Minami, Yudai Yamazaki, Junich Meguro, Eijiro Takeuchi, Yoshiki Ninomiya, Shinpei Kato, Masato Edahiro
Publikováno v:
International Journal of Automotive Engineering, Vol 13, Iss 4, Pp 206-213 (2022)
ABSTRACT: Ego-vehicle localization is a critical technology in autonomous driving systems, and one of the widely used methods for localization is scan matching between a 3D map and real-time LiDAR scan. This method is known to fail due to factors suc
Externí odkaz:
https://doaj.org/article/c0d58a8a1263421fadae6c6ccfe26b8b
Publikováno v:
IEEE Access, Vol 10, Pp 57759-57782 (2022)
As the operational domain of autonomous vehicles expands, encountering occlusions during navigation becomes unavoidable. Most of the existing research on occlusion-aware motion planning focuses only on the longitudinal motion of the ego vehicle and n
Externí odkaz:
https://doaj.org/article/c970cc11e3b9468fa8a6b2e8223281c4
Publikováno v:
Nihon Kikai Gakkai ronbunshu, Vol 86, Iss 892, Pp 20-00151-20-00151 (2020)
Localization in autonomous vehicles is an important technology, and the use of 3D point clouds, which provide accurate information on the road surroundings, has been attracting attention to help improve localization. In recent years, many methods for
Externí odkaz:
https://doaj.org/article/69ccfb8f1bd04a90a1df6288d0f9bbfb
Autor:
Yoshiki Ninomiya, Bihong Fu
Publikováno v:
Geosciences, Vol 6, Iss 3, p 39 (2016)
The mineralogical indices the Quartz Index (QI), Carbonate Index (CI) and Mafic Index (MI) for ASTER multispectral thermal infrared (TIR) data were applied to various geological materials for regional lithological mapping on the Tibetan Plateau. Many
Externí odkaz:
https://doaj.org/article/be0e8ac5cf6b42a3aa843032f7ade8e8
Publikováno v:
Journal of Robotics and Mechatronics. 35:435-444
To realize autonomous vehicle safety, it is important to accurately estimate the vehicle’s pose. As one of the localization techniques, 3D point cloud registration is commonly used. However, pose errors are likely to occur when there are few featur
How to monitor multiple autonomous vehicles remotely with few observers: An active management method
Autor:
Ming Ding, Nobuo Kawaguchi, Yoshiki Ninomiya, Eijiro Takeuchi, Kazuya Takeda, Yoshio Ishiguro
Publikováno v:
2021 IEEE Intelligent Vehicles Symposium (IV).
In this research, we proposed an active management method to tele-monitor and tele-operate more autonomous vehicles (AVs) with few observers by adjusting the movement of the AVs actively. A management system is created to get the status from the AVs
Autor:
Yoshiki Ninomiya, Bihong Fu
Publikováno v:
Ore Geology Reviews. 108:54-72
The major minerals forming the Earth’s crust exhibit characteristic spectral properties in the thermal infrared (TIR; 7–14 µm) region of the spectrum, although most of them have few features in the visible and near infrared (0.4–2.5 µm) regio
Publikováno v:
Electronics
Volume 10
Issue 4
Electronics, Vol 10, Iss 411, p 411 (2021)
Volume 10
Issue 4
Electronics, Vol 10, Iss 411, p 411 (2021)
A common approach used for planning blind intersection crossings is to assume that hypothetical vehicles are approaching the intersection at a constant speed from the occluded areas. Such an assumption can result in a deadlock problem, causing the eg
Publikováno v:
ITSC
As the autonomy level of self-driving vehicles increases, they will be expected to operate safely in increasingly complex environments. During real-world driving, occlusions are inevitable. Therefore, the ability to accurately identify the visible an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2de9b0e23c845b2dd9e88ddcfbe95d4