{"title":"基于优化卷积神经网络的人形机器人目标识别","authors":"Xiao Ming, Xiao Nanfeng, Zeng Mengjun, Yuan Qunyong","doi":"10.36959/673/363","DOIUrl":null,"url":null,"abstract":"In recent years, many researchers have proposed a series of algorithms based on convolutional neural networks and achieved good performances in the field of object detection and recognition. For humanoid robots, they are designed to assist or replace people in completing a series of anthropomorphic tasks, and their ability to recognize and grasp surrounding objects is the most basic requirement.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimized Convolutional Neural Network-Based Object Recognition for Humanoid Robot\",\"authors\":\"Xiao Ming, Xiao Nanfeng, Zeng Mengjun, Yuan Qunyong\",\"doi\":\"10.36959/673/363\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, many researchers have proposed a series of algorithms based on convolutional neural networks and achieved good performances in the field of object detection and recognition. For humanoid robots, they are designed to assist or replace people in completing a series of anthropomorphic tasks, and their ability to recognize and grasp surrounding objects is the most basic requirement.\",\"PeriodicalId\":73286,\"journal\":{\"name\":\"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36959/673/363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36959/673/363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimized Convolutional Neural Network-Based Object Recognition for Humanoid Robot
In recent years, many researchers have proposed a series of algorithms based on convolutional neural networks and achieved good performances in the field of object detection and recognition. For humanoid robots, they are designed to assist or replace people in completing a series of anthropomorphic tasks, and their ability to recognize and grasp surrounding objects is the most basic requirement.