{"title":"基于自适应学习率衰减的视网膜网车辆类型检测","authors":"Yiliu Xu, Peng He, Hui Wang, Ting Dong, Pan Shao","doi":"10.2316/J.2021.206-0625","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":54943,"journal":{"name":"International Journal of Robotics & Automation","volume":"103 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"VEHICLE TYPE DETECTION BASED ON RETINANET WITH ADAPTIVE LEARNING RATE ATTENUATION\",\"authors\":\"Yiliu Xu, Peng He, Hui Wang, Ting Dong, Pan Shao\",\"doi\":\"10.2316/J.2021.206-0625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":54943,\"journal\":{\"name\":\"International Journal of Robotics & Automation\",\"volume\":\"103 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Robotics & Automation\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.2316/J.2021.206-0625\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Robotics & Automation","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.2316/J.2021.206-0625","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
期刊介绍:
First published in 1986, the International Journal of Robotics and Automation was one of the inaugural publications in the field of robotics. This journal covers contemporary developments in theory, design, and applications focused on all areas of robotics and automation systems, including new methods of machine learning, pattern recognition, biologically inspired evolutionary algorithms, fuzzy and neural networks in robotics and automation systems, computer vision, autonomous robots, human-robot interaction, microrobotics, medical robotics, mobile robots, biomechantronic systems, autonomous design of robotic systems, sensors, communication, and signal processing.