{"title":"基于卷积神经网络的物体检测和人脸识别的社交辅助机器人交互","authors":"Dendi Hazik Fuadi, D. Novita, Mohammad Taufik","doi":"10.1109/AIMS52415.2021.9466091","DOIUrl":null,"url":null,"abstract":"The technology of robots has developed to help humans in many ways. It is not only limited to assist but also to interact socially with humans. Robots can interact socially with humans by utilizing the concept of artificial intelligence based on machine learning. In this paper, the prototype of Socially Assistive Robot (SAR) implemented artificial intelligence by using object detection and face recognition based on convolutional neural network and communication reports to Telegram Apps. To interact verbally, Google Assistant was required. The prototype was a successfully created and social interaction robot with an average face recognition accuracy is 85.41%.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Socially Assistive Robot Interaction by Objects Detection and Face Recognition on Convolutional Neural Network for Parental Monitoring\",\"authors\":\"Dendi Hazik Fuadi, D. Novita, Mohammad Taufik\",\"doi\":\"10.1109/AIMS52415.2021.9466091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The technology of robots has developed to help humans in many ways. It is not only limited to assist but also to interact socially with humans. Robots can interact socially with humans by utilizing the concept of artificial intelligence based on machine learning. In this paper, the prototype of Socially Assistive Robot (SAR) implemented artificial intelligence by using object detection and face recognition based on convolutional neural network and communication reports to Telegram Apps. To interact verbally, Google Assistant was required. The prototype was a successfully created and social interaction robot with an average face recognition accuracy is 85.41%.\",\"PeriodicalId\":299121,\"journal\":{\"name\":\"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIMS52415.2021.9466091\",\"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 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIMS52415.2021.9466091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Socially Assistive Robot Interaction by Objects Detection and Face Recognition on Convolutional Neural Network for Parental Monitoring
The technology of robots has developed to help humans in many ways. It is not only limited to assist but also to interact socially with humans. Robots can interact socially with humans by utilizing the concept of artificial intelligence based on machine learning. In this paper, the prototype of Socially Assistive Robot (SAR) implemented artificial intelligence by using object detection and face recognition based on convolutional neural network and communication reports to Telegram Apps. To interact verbally, Google Assistant was required. The prototype was a successfully created and social interaction robot with an average face recognition accuracy is 85.41%.