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ERIC Number: ED626897
Record Type: Non-Journal
Publication Date: 2022
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Toward Better Driving with Gaze Awareness Environment Supported by Area Segmentation
Yamada, Taketo; Matsuura, Kenji; Takeuchi, Hironori; Kashihara, Akihiro; Yamasaki, Kenichi; Kurita, Genta
International Association for Development of the Information Society, Paper presented at the International Conference on Cognition and Exploratory Learning in Digital Age (CELDA) (19th, 2022)
It is important to make car-drivers improve their way of looking for recognizing key objects or areas precisely. This study designs a system following such a motivation that distinguishes several areas in a display with weights of importance. A present proposing function for successful area detection offers drivers an opportunity to compare their gaze with experts. Concrete method for this implementation includes U-Net that is one of major techniques of machine learning combined with grid segmentation.
International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org
Publication Type: Speeches/Meeting Papers; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: International Association for Development of the Information Society (IADIS)
Grant or Contract Numbers: N/A
Author Affiliations: N/A