基于多元时间序列的可解释AI汽车碰撞检测

2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) Pub Date : 2021-10-29 DOI:10.1109/ICCICC53683.2021.9811335

L. Tronchin, R. Sicilia, E. Cordelli, L. R. Celsi, D. Maccagnola, Massimo Natale, P. Soda

{"title":"基于多元时间序列的可解释AI汽车碰撞检测","authors":"L. Tronchin, R. Sicilia, E. Cordelli, L. R. Celsi, D. Maccagnola, Massimo Natale, P. Soda","doi":"10.1109/ICCICC53683.2021.9811335","DOIUrl":null,"url":null,"abstract":"The pervasiveness of Artificial Intelligence approaches in effectively supporting the decision process in many applications has raised the need to explain their behaviour. In this context, we present the application and evaluation of three eXplainable Artificial Intelligence methods in a real-world multimodal task of anomaly detection on telematics data. We cope with the challenge of explaining Multivariate Time Series and of translating methods designed for images to this domain.","PeriodicalId":101653,"journal":{"name":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Explainable AI for Car Crash Detection using Multivariate Time Series\",\"authors\":\"L. Tronchin, R. Sicilia, E. Cordelli, L. R. Celsi, D. Maccagnola, Massimo Natale, P. Soda\",\"doi\":\"10.1109/ICCICC53683.2021.9811335\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The pervasiveness of Artificial Intelligence approaches in effectively supporting the decision process in many applications has raised the need to explain their behaviour. In this context, we present the application and evaluation of three eXplainable Artificial Intelligence methods in a real-world multimodal task of anomaly detection on telematics data. We cope with the challenge of explaining Multivariate Time Series and of translating methods designed for images to this domain.\",\"PeriodicalId\":101653,\"journal\":{\"name\":\"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCICC53683.2021.9811335\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCICC53683.2021.9811335","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

人工智能方法在许多应用程序中有效地支持决策过程的普及，提出了解释其行为的需要。在此背景下，我们提出了三种可解释的人工智能方法在远程信息处理数据异常检测的实际多模态任务中的应用和评估。我们应对解释多元时间序列的挑战，并将为图像设计的方法翻译到这个领域。

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

Explainable AI for Car Crash Detection using Multivariate Time Series

The pervasiveness of Artificial Intelligence approaches in effectively supporting the decision process in many applications has raised the need to explain their behaviour. In this context, we present the application and evaluation of three eXplainable Artificial Intelligence methods in a real-world multimodal task of anomaly detection on telematics data. We cope with the challenge of explaining Multivariate Time Series and of translating methods designed for images to this domain.

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

2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

自引率

0.00%

发文量