Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Sakura Kadowaki"'
Publikováno v:
2019 19th International Conference on Control, Automation and Systems (ICCAS).
Research and development of automatic driving have been progressing actively. Level 3 autonomous driving requires shifting of driving activity between the system and a driver. Such shifting poses high risks of a severe traffic accident if a driver is
Publikováno v:
ISPACS
Modern society is said to be a stress society. With increased mental illness such as depression, implementation of stress check systems has become mandatory. However, in stress check systems, objective diagnostic results are sought to avoid difficult
Publikováno v:
GCCE
This study analyzed causes of driving in the wrong direction on a roadway (reverse running) and developed a gaze control algorithm to inform a driver of priority targets that demand attention to prevent reverse running: highpriority gazing objects (H
Publikováno v:
SMC
For this study, using Bayesian Network (BN) to graphically express the interrelationship between safety confirmation behaviors for driving scene and driver's internal state, we analyze correlations between characteristic body information (i.e., eye-g
Publikováno v:
Journal of Japan Society for Fuzzy Theory and Intelligent Informatics. 23:157-169
本論文では,表情空間の動的多様性を定量化する表情空間チャートという枠組みを提案する.表情空間チャートは,「喜び」,「怒り」,「悲しみ」の3表情を対象として,各表情の覚
Publikováno v:
ICVES
For this study, we defined a "concentration state" when a driver performs only driving tasks, and a "distraction state" when a driver performs a driving task and a mental arithmetic task simultaneously. From results of these driving tests, we elucida
Publikováno v:
2013 IEEE International Conference on Mechatronics and Automation.
This paper presents a gender-specific stress model to analyze the psychological stress factors on intentional facial expressions. We have focused on the relationship between facial expression intensity and Stress Response Scale (SRS-18). In this pape
Publikováno v:
ISABEL
As described herein, we propose an unsupervised method for segmentation of magnetic resonance (MR) brain images by hybridizing the self-mapping characteristics of 1-D Self-Organizing Maps (SOMs) and using incremental learning functions of fuzzy Adapt
Publikováno v:
IEEE Nuclear Science Symposuim & Medical Imaging Conference.
As described herein, we propose an unsupervised method for segmentation of magnetic resonance (MR) brain images by hybridizing the self-mapping characteristics of 1-D Self-Organizing Maps (SOMs) and using incremental learning functions of fuzzy Adapt
Publikováno v:
IJCNN
We propose an objective segmentation method for Magnetic Resonance (MR) images of the brain using self-mapping characteristics of one-dimensional Self-Organizing Maps (SOM). The proposed method requires no operators to specify the representative poin