Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Tokihiko Akita"'
Publikováno v:
International Journal of Automotive Engineering, Vol 13, Iss 2, Pp 97-102 (2022)
We research parking scene reconstruction by a deep neural network (DNN) using a millimeter-wave radar. High accuracy can be achieved for the training dataset; however, it is degraded on untrained data. It is an unavoidable challenge of generalizabili
Externí odkaz:
https://doaj.org/article/14f5fdeea84d4099b1e5f431256eb735
Autor:
Tokihiko Akita, Yuya Yamada
Publikováno v:
International Journal of Automotive Engineering, Vol 5, Iss 3, Pp 101-108 (2014)
Image recognition of vehicles is still difficult for practical use under various actual environments. Recently machine learning algorithm utilizing general feature amount have been often adopted. However, they utilize only a part of information obtai
Externí odkaz:
https://doaj.org/article/dd3660497d344d8a8efbd80e4dc45a00
Autor:
Tokihiko Akita, Hiroto Shirahige, Hong Seunghee, Jun’ichiro Hayashi, Keisuke Suzuki, Shun’ichi Doi
Publikováno v:
International Journal of Automotive Engineering, Vol 5, Iss 2, Pp 65-71 (2014)
Crossing collisions caused by cognitive error often occur at unsignalized intersections. For the countermeasure, driver assistant systems that warn a driver against stop sign violation are researched and commercialized. However, if a driver is warned
Externí odkaz:
https://doaj.org/article/b7d2d501d95b4741acb41be5d5ce51a7
Publikováno v:
Journal of Robotics and Mechatronics. 32:494-502
The frequency of pedestrian traffic accidents continues to increase in Japan. Thus, a driver assistance system is expected to reduce the number of accidents. However, it is difficult for the current environmental recognition sensors to detect crossin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fb31327cb8ecce5b400deeac97cdccb
https://doi.org/10.20965/jrm.2020.p0494
https://doi.org/10.20965/jrm.2020.p0494
Publikováno v:
2021 IEEE Intelligent Vehicles Symposium (IV).
Local image features matching is a useful technique for 3D reconstruction and localization in ITS field. In recent years, machine learning-based local feature matching methods have been proposed. However, it is impractical to manually generate the gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a8773ceb2f3bcaf5b57429a559a8c3d
https://doi.org/10.1109/iv48863.2021.9575947
https://doi.org/10.1109/iv48863.2021.9575947
Publikováno v:
2021 IEEE Intelligent Vehicles Symposium (IV).
Deep Neural Network (DNN) can provide highly accurate recognition for trained data, however, the estimation error for untrained data cannot be controlled. This is an essential challenge of generalizability in machine learning, and it is difficult to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b59885dcc14fb10d59ae425ab65bbc2f
https://doi.org/10.1109/iv48863.2021.9575743
https://doi.org/10.1109/iv48863.2021.9575743
Publikováno v:
ITSC
Vehicle ego-localization using in-vehicle sensors is one of the most important technologies for ADAS and AD. Accordingly, various attempts for accurate localization using in-vehicle sensors have been developed. Methods using a visible-light camera or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2651c37336057a3edc1cbdb7f7a965fb
https://doi.org/10.1109/itsc45102.2020.9294170
https://doi.org/10.1109/itsc45102.2020.9294170
Autor:
Seiichi Mita, Tokihiko Akita
Publikováno v:
ITSC
A millimeter-wave radar has major advantages in robustness under adverse weather and illumination conditions. However, it has some concerns regarding signal noise and resolution. They make it difficult for the radar to precisely recognize the driving
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5b409139a570352c2a8e71c1b048c49
https://doi.org/10.1109/itsc45102.2020.9294210
https://doi.org/10.1109/itsc45102.2020.9294210
Autor:
Seiichi Mita, Tokihiko Akita
Publikováno v:
ITSC
All-weather sensors are necessary to realize automated driving level 3 or more, one of which is a millimeter-wave radar. However, the radar has some issues such as low space resolution and noisy signal. In order to solve them, stochastic processing i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2f6cf557431895320f4931ea67be3d4
https://doi.org/10.1109/itsc.2019.8917144
https://doi.org/10.1109/itsc.2019.8917144
Publikováno v:
ITSC
Recently, automated emergency brake systems for pedestrian have been commercialized. However, they cannot detect crossing pedestrians when turning at intersections because the field of view is not wide enough. Thus, we propose to utilize a surround v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce56663a6f41ecbad2c6d21ea2179427
https://doi.org/10.1109/itsc.2018.8569716
https://doi.org/10.1109/itsc.2018.8569716