{"title":"将深度学习、验证和基于场景的编程结合起来","authors":"Guy Katz, Achiya Elyasaf","doi":"10.1145/3459086.3459631","DOIUrl":null,"url":null,"abstract":"Deep learning (DL) [4] is dramatically changing the world of software. The rapid improvement in deep neural network (DNN) technology now enables engineers to train models that achieve superhuman results, often surpassing algorithms that have been carefully hand-crafted by domain experts [19, 20]. There is even an intensifying trend of incorporating DNNs in safety-critical systems, e.g. as controllers for autonomous vehicles and drones [1, 12].","PeriodicalId":127610,"journal":{"name":"Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Towards combining deep learning, verification, and scenario-based programming\",\"authors\":\"Guy Katz, Achiya Elyasaf\",\"doi\":\"10.1145/3459086.3459631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning (DL) [4] is dramatically changing the world of software. The rapid improvement in deep neural network (DNN) technology now enables engineers to train models that achieve superhuman results, often surpassing algorithms that have been carefully hand-crafted by domain experts [19, 20]. There is even an intensifying trend of incorporating DNNs in safety-critical systems, e.g. as controllers for autonomous vehicles and drones [1, 12].\",\"PeriodicalId\":127610,\"journal\":{\"name\":\"Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3459086.3459631\",\"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 1st International Workshop on Verification of Autonomous & Robotic Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3459086.3459631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards combining deep learning, verification, and scenario-based programming
Deep learning (DL) [4] is dramatically changing the world of software. The rapid improvement in deep neural network (DNN) technology now enables engineers to train models that achieve superhuman results, often surpassing algorithms that have been carefully hand-crafted by domain experts [19, 20]. There is even an intensifying trend of incorporating DNNs in safety-critical systems, e.g. as controllers for autonomous vehicles and drones [1, 12].
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