SDCDNet: A Semi-Dual Change Detection Network Framework With Super-Weak Label for Remote Sensing Image

Author:

Wang Jiahao1ORCID,Liu Fang1ORCID,Wang Hao1,Liu Xu1ORCID,Jiao Licheng1ORCID,Yang Hua1ORCID,Li Lingling1ORCID,Chen Puhua1ORCID

Affiliation:

1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Joint International Research Laboratory of Intelligent Perception and Computation, School of Artificial Intelligence, Xidian University, Xi’an, China

Funder

National Natural Science Foundation of China

Key Research and Development Program in Shaanxi Province of China

State Key Program of National Natural Science of China

Program for Cheung Kong Scholars and Innovative Research Team in University

Fund for Foreign Scholars in University Research and Teaching Programs

Key Scientific Technological Innovation Research Project by the Ministry of Education

National Key Research and Development Program of China

CAAI Huawei MindSpore Open Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Reference75 articles.

1. Integrating remote sensing and machine learning into environmental monitoring and assessment of land use change

2. Revisiting consistency regularization for semi-supervised change detection in remote sensing images;bandara;arXiv 2204 08454,2022

3. Remote Sensing of Environment: History, Philosophy, Approach and Contributions, 1969 –2019

4. Fully convolutional change detection framework with generative adversarial network for unsupervised, weakly supervised and regional supervised change detection;wu;arXiv 2201 06030,2022

5. Deep Learning for Change Detection in Remote Sensing Images: Comprehensive Review and Meta-Analysis

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