Automated object recognition in high-resolution optical remote sensing imagery

作     者：Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang Yazhou Yao;Tao Chen;Hanbo Bi;Xinhao Cai;Gensheng Pei;Guoye Yang;Zhiyuan Yan;Xian Sun;Xing Xu;Hai Zhang

作者机构：School of Computer Science and EngineeringNanjing University of Science and Technology Aerospace Information Research InstituteChinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University 

出 版 物：《National Science Review》 (国家科学评论(英文版))

年 卷 期：2023年第10卷第6期

页      面：38-41页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081002[工学-信号与信息处理] 

基　　金：supported in part by the International Society for Photogrammetry and Remote (ISPRS)Scientific Initiatives 2021 in part by the National Natural Science Foundation of China (62171436 and 62102182) in part by the Natural Science Foundation of Jiangsu Province (BK20210327 and BK20220934) in part by the China Postdoctoral Science Foundation (2022M711635) 

摘      要：INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely accessible.The automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the field.It provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.