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An end-to-end multiple side-outputs fusion deep supervision network based remote sensing image change detection algorithm

  • Published:2023-12 Issue: Volume:213 Page:109203
  • ISSN:0165-1684
  • Container-title:Signal Processing
  • language:en
  • Short-container-title:Signal Processing

Author:

Wu Xiaosuo,Yang Le,Ma Yaya,Wu Chaoyang,Guo Cunge,Yan Haowen,Qiao Ze,Yao Shuang,Fan Yufeng

Funder

National Key Research and Development Program of China

Lanzhou Jiaotong University

Science and Technology Department of Gansu Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference54 articles.

1. Review and prospect in change detection of multi-temporal remote sensing images;Zhang;Acta Geodaet. Cartogr. Sin.,2022

2. Remote sensing satellite's attitude control system: rapid performance sizing for passive scan imaging mode;Kosari;Aircraft Eng. Aerospace Technol.,2020

3. Forest biomass estimation using synthetic aperture radar polarimetric features;Sharifi;J. Appl. Rem. Sens.,2015

4. Estimation of biophysical parameters in wheat crops in Golestan province using ultra-high resolution images;Sharifi;Rem. Sens. Lett.,2018

5. Estimation of forest biomass using multivariate relevance vector regression;Sharifi;Photogramm. Eng. Rem. Sens.,2016

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1. TMLNet: Triad Multitask Learning Network for multiobjective based change detection;Neurocomputing;2024-09

2. Ultrasound Image Segmentation using a Model of Transformer and DFT;2024 IEEE UFFC Latin America Ultrasonics Symposium (LAUS);2024-05-08

3. Research on road surface crack detection based on SegNet network;Journal of Engineering and Applied Science;2024-03-01

4. MLANet: a multi-level attention-based change detection method for remote sensing images;Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023);2024-02-21

5. A Review: Remote Sensing Image Object Detection Algorithm Based on Deep Learning;Electronics;2023-12-06
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