Consistency-guided lightweight network for semi-supervised binary change detection of buildings in remote sensing images-Reference-Cited by-同舟云学术

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Consistency-guided lightweight network for semi-supervised binary change detection of buildings in remote sensing images

Published:2023-09-19 Issue:1 Volume:60 Page:
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Ding Qing¹,Shao Zhenfeng¹,Huang Xiao²,Feng Xiaoxiao³,Altan Orhan⁴,Hu Bin¹

Affiliation:

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

2. Department of Geosciences, University of Arkansas, Fayetteville, AR, USA

3. School of Computer Science, Hubei University of Technology, Wuhan, China

4. Department of Geomatics Engineering, Istanbul Technical University, Istanbul, Turkey

Funder

National Natural Science Foundation of China

03 special research and 5G project of Jiangxi Province in China

Hubei key R&D plan

Key R&D project of Sichuan science and technology plan

Zhuhai industry university research cooperation project of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2023.2257980

Reference77 articles.

1. A Multi-Feature Fusion Using Deep Transfer Learning for Earthquake Building Damage Detection

2. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

3. Automatic analysis of the difference image for unsupervised change detection

4. Albumentations: Fast and Flexible Image Augmentations

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MLFA-Net: multi-level feature-aggregated network for semantic change detection in remote sensing images;International Journal of Digital Earth;2024-09-09

2. Dynamically Updated Semi-Supervised Change Detection Network Combining Cross-Supervision and Screening Algorithms;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Dual-Channel Semi-Supervised Adversarial Network for Building Segmentation from UAV-Captured Images;Remote Sensing;2023-12-02

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