Yiting He, Xiaoyi Fan, Feng Wang, Fangxin Wang, Jiangchuan Liu
{"title":"基于边缘计算的生成对抗网络用于实时道路感知","authors":"Yiting He, Xiaoyi Fan, Feng Wang, Fangxin Wang, Jiangchuan Liu","doi":"10.1109/IWQoS.2018.8624148","DOIUrl":null,"url":null,"abstract":"Automobiles have become one of the necessities of modern life and deeply penetrated into our daily activities. They unfortunately also introduce numerous social problems, among which traffic accidents are most notoriously threatening automobile drivers and other road users. Advanced driver-assistance systems (ADAS) are under rapid development in recent years, which can necessarily reduce or even eliminate the driver errors, significantly relieving on drivers suffering or stress. These state-of-the-art ADAS mainly rely on built-in cameras, radars and ultrasound sensors to provide road sensing services for object detection, which are further advanced by recent explosion of vision and neural network technologies.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Edge Computing Empowered Generative Adversarial Networks for Realtime Road Sensing\",\"authors\":\"Yiting He, Xiaoyi Fan, Feng Wang, Fangxin Wang, Jiangchuan Liu\",\"doi\":\"10.1109/IWQoS.2018.8624148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automobiles have become one of the necessities of modern life and deeply penetrated into our daily activities. They unfortunately also introduce numerous social problems, among which traffic accidents are most notoriously threatening automobile drivers and other road users. Advanced driver-assistance systems (ADAS) are under rapid development in recent years, which can necessarily reduce or even eliminate the driver errors, significantly relieving on drivers suffering or stress. These state-of-the-art ADAS mainly rely on built-in cameras, radars and ultrasound sensors to provide road sensing services for object detection, which are further advanced by recent explosion of vision and neural network technologies.\",\"PeriodicalId\":222290,\"journal\":{\"name\":\"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWQoS.2018.8624148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2018.8624148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge Computing Empowered Generative Adversarial Networks for Realtime Road Sensing
Automobiles have become one of the necessities of modern life and deeply penetrated into our daily activities. They unfortunately also introduce numerous social problems, among which traffic accidents are most notoriously threatening automobile drivers and other road users. Advanced driver-assistance systems (ADAS) are under rapid development in recent years, which can necessarily reduce or even eliminate the driver errors, significantly relieving on drivers suffering or stress. These state-of-the-art ADAS mainly rely on built-in cameras, radars and ultrasound sensors to provide road sensing services for object detection, which are further advanced by recent explosion of vision and neural network technologies.