{"title":"自动驾驶的深度学习","authors":"Nicholas Burleigh, Jordan King, T. Bräunl","doi":"10.1109/DICTA47822.2019.8945818","DOIUrl":null,"url":null,"abstract":"In this paper we look at Deep Learning methods using TensorFlow for autonomous driving tasks. Using scale model vehicles in a traffic scenario similar to the Audi Autonomous Driving Cup and the Carolo Cup, we successfully used Deep Learning stacks for the two independent tasks of lane keeping and traffic sign recognition.","PeriodicalId":6696,"journal":{"name":"2019 Digital Image Computing: Techniques and Applications (DICTA)","volume":"21 1","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Deep Learning for Autonomous Driving\",\"authors\":\"Nicholas Burleigh, Jordan King, T. Bräunl\",\"doi\":\"10.1109/DICTA47822.2019.8945818\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we look at Deep Learning methods using TensorFlow for autonomous driving tasks. Using scale model vehicles in a traffic scenario similar to the Audi Autonomous Driving Cup and the Carolo Cup, we successfully used Deep Learning stacks for the two independent tasks of lane keeping and traffic sign recognition.\",\"PeriodicalId\":6696,\"journal\":{\"name\":\"2019 Digital Image Computing: Techniques and Applications (DICTA)\",\"volume\":\"21 1\",\"pages\":\"1-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Digital Image Computing: Techniques and Applications (DICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA47822.2019.8945818\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Digital Image Computing: Techniques and Applications (DICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA47822.2019.8945818","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we look at Deep Learning methods using TensorFlow for autonomous driving tasks. Using scale model vehicles in a traffic scenario similar to the Audi Autonomous Driving Cup and the Carolo Cup, we successfully used Deep Learning stacks for the two independent tasks of lane keeping and traffic sign recognition.
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