Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Naohiro Fukumura"'
Publikováno v:
IEEE Access, Vol 9, Pp 92003-92016 (2021)
Driving vehicles requires mastery of a multitude of tasks. Among these, parking is one task that most drivers feel they are not as skilled as they would like to be. In this paper, we focus on improvement of reverse perpendicular parking performance.
Externí odkaz:
https://doaj.org/article/dc602672f7044b5b9aeca0dcaeea7ed1
Publikováno v:
2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS).
Publikováno v:
IEEE Access. 9:92003-92016
Driving vehicles requires mastery of a multitude of tasks. Among these, parking is one task that most drivers feel they are not as skilled as they would like to be. In this paper, we focus on improvement of reverse perpendicular parking performance.
Autor:
Motoi Matsuda, Naohiro Fukumura
Publikováno v:
2020 7th International Conference on Advance Informatics: Concepts, Theory and Applications (ICAICTA).
Manipulation control technology for multi-fingered robot hands is an important requirement of life-support robots operating in living spaces. However, Hand movements with many degrees of freedom are difficult to replicate. When humans grasp an object
Autor:
Naohiro Fukumura, Shota Shirakawa
Publikováno v:
2017 International Conference on Advanced Informatics, Concepts, Theory, and Applications (ICAICTA).
In Deep Learning, which has become a topic of intense study in recent years, an auto encoder that learns an identity map by a neural network plays an important role to extract features of data. One disadvantage of this method is that it is not always
Publikováno v:
Electrical Engineering in Japan. 161:38-48
A forward-propagation learning rule (FPL) has been proposed for a neural network (NN) to learn an inverse model of a controlled object. A feature of FPL is that the trajectory error propagates forward in NN and appropriate values of two learning para
Publikováno v:
Systems and Computers in Japan. 37:54-66
Publikováno v:
The Brain & Neural Networks. 13:101-110
A forward-propagation learning rule (FPL) has been proposed for acquiring neural inverse models without back-propagated signals based on a Newton-like method. A modified multiple linear regression, RLS algorithms or a Fisher's scoring method have bee
Publikováno v:
Systems and Computers in Japan. 36:1-12
Publikováno v:
Systems and Computers in Japan. 36:71-80