基于CNN和NASS-CDS数据的交通事故伤害等级分类研究

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI:10.1145/3301326.3301378

H. Song, Yongbeom Lee, Seongkeun Park, Hyeonseok Kim, Eungi Cho, Mingyu Park, Seung-Woo Kim

{"title":"基于CNN和NASS-CDS数据的交通事故伤害等级分类研究","authors":"H. Song, Yongbeom Lee, Seongkeun Park, Hyeonseok Kim, Eungi Cho, Mingyu Park, Seung-Woo Kim","doi":"10.1145/3301326.3301378","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new occupant injury prediction algorithm using real car accident data base, NASS-CDS DB. Field crash data which are collected by IIHS is used as input of convolutional neural network to estimate occupant injury. And in order to applying CNN, we are encoding crash information data as two dimensional image. Our experiment results can be shown the validity of our proposed algorithm.","PeriodicalId":294040,"journal":{"name":"Proceedings of the 2018 VII International Conference on Network, Communication and Computing","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Study on Classification of Traffic Accident Injury Grade Using CNN and NASS-CDS Data\",\"authors\":\"H. Song, Yongbeom Lee, Seongkeun Park, Hyeonseok Kim, Eungi Cho, Mingyu Park, Seung-Woo Kim\",\"doi\":\"10.1145/3301326.3301378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new occupant injury prediction algorithm using real car accident data base, NASS-CDS DB. Field crash data which are collected by IIHS is used as input of convolutional neural network to estimate occupant injury. And in order to applying CNN, we are encoding crash information data as two dimensional image. Our experiment results can be shown the validity of our proposed algorithm.\",\"PeriodicalId\":294040,\"journal\":{\"name\":\"Proceedings of the 2018 VII International Conference on Network, Communication and Computing\",\"volume\":\"107 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 VII International Conference on Network, Communication and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3301326.3301378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 VII International Conference on Network, Communication and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3301326.3301378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

本文基于NASS-CDS数据库，提出了一种新的乘员伤害预测算法。利用IIHS采集的现场碰撞数据作为卷积神经网络的输入，对乘员损伤进行估计。为了应用CNN，我们将坠机信息数据编码为二维图像。实验结果表明了该算法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Study on Classification of Traffic Accident Injury Grade Using CNN and NASS-CDS Data

In this paper, we propose a new occupant injury prediction algorithm using real car accident data base, NASS-CDS DB. Field crash data which are collected by IIHS is used as input of convolutional neural network to estimate occupant injury. And in order to applying CNN, we are encoding crash information data as two dimensional image. Our experiment results can be shown the validity of our proposed algorithm.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the 2018 VII International Conference on Network, Communication and Computing

自引率

0.00%

发文量