Semisupervised Change Detection With Feature-Prediction Alignment-Reference-Cited by-同舟云学术

Semisupervised Change Detection With Feature-Prediction Alignment

Published:2023 Issue: Volume:61 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Xueting¹,Huang Xin²^ORCID,Li Jiayi¹

Affiliation:

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

2. School of Remote Sensing and Information Engineering and State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

Funder

National Natural Science Foundation of China

Special Fund of Hubei Luojia Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10049565.pdf?arnumber=10049565

Reference59 articles.

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

2. Randaugment: Practical automated data augmentation with a reduced search space

3. SemiCDNet: A Semisupervised Convolutional Neural Network for Change Detection in High Resolution Remote-Sensing Images

4. CHANGE DETECTION IN REMOTE SENSING IMAGES USING CONDITIONAL ADVERSARIAL NETWORKS

5. Dropout: A simple way to prevent neural networks from overfitting;srivastava;J Mach Learn Res,2014

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