Large-Scope PolSAR Image Change Detection Based on Looking-Around-and-Into Mode

著录项

• 来源
  《IEEE Transactions on Geoscience and Remote Sensing》 |2021年第1期|363-378|共16页
• 作者

  Fang Liu; Xu Tang; Xiangrong ZhangLicheng JiaoJia Liu;

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• 作者单位

  Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China;

  Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi’an, China;

  Department of Electronic Engineering, National Key laboratory for Radar Signal Processing and Institute of Intelligent Information Processing, Xidian University, Xi’an, ChinaSchool of Electronic Engineering, Xidian University, Xi’an, ChinaSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China;

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• 收录信息
• 原文格式 PDF
• 正文语种 英语
• 中图分类 地球物理学;遥感技术;
• 关键词

  Task analysis; Shape; Visualization; Image segmentation; Polarimetric synthetic aperture radar; Proposals; Convolutional neural networks; Attention proposal network (APN); change detection; large-scope Polarimetric Synthetic Aperture Radar~(PolSAR) image; Looking-Around-and-Into (LAaI); recurrent convolutional neural network (CNN) (Recurrent CNN)looseness-1;