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Summary & Details

Construction of a Vehicle Damage Level Recognition Model based on Deep Learning

深層学習に基づく車両損壊程度認識モデルの構築

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Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20225045

Paper/Info type: Proceedings (Spring)

No.11-22

Pages: 1-4(Total 4 p)

Date of publication: May 2022

Publisher: JSAE

Language: Japanese

Event: 2022 JSAE Annual Congress (Spring)

Detailed Information

Author(J)	1) 中尾賢人, 2) 西本哲也, 3) 本村友一
Author(E)	1) Kento Nakao, 2) Tetsuya Nishimoto, 3) Tomokazu Motomura
Affiliation(J)	1) 日本大学, 2) 日本大学, 3) 日本医科大学千葉北総病院
Affiliation(E)	1) Nihon University, 2) Nihon University, 3) Nippon Medical School, Chiba Hokusoh Hospital
Abstract(J)	先進事故自動通報システムにおける事故発生後のドクターヘリを要請するかの判断を画像認識により行うことを目的として日本大学・日本医科大学による交通事故実態調査で得られた車両損壊画像をもとに深層学習に基づく車両の損壊程度認識モデルを構築及び検証を行った．車両損壊程度認識モデルの結果について述べる． Translation
Abstract(E)	Using image recognition to decide whether to call for a helicopter after an accident can reduce the burden on paramedics. In this paper, we constructed a model for recognizing the degree of damage to a vehicle based on deep learning. We used images of vehicle damage obtained from a traffic accident survey conducted by Nihon University and Nippon Medical School. The results of the model are described.

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