MSF-Net: A Multiscale Supervised Fusion Network for Building Change Detection in High-Resolution Remote Sensing Images-Reference-Cited by-同舟云学术

MSF-Net: A Multiscale Supervised Fusion Network for Building Change Detection in High-Resolution Remote Sensing Images

Published:2022 Issue: Volume:10 Page:30925-30938
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Chen Jiahao¹^ORCID,Fan Junfu¹^ORCID,Zhang Mengzhen¹^ORCID,Zhou Yuke²^ORCID,Shen Chen³

Affiliation:

1. School of Civil and Architectural Engineering, Shandong University of Technology, Zibo, China

2. Ecology Observing Network and Modeling Laboratory, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

3. Shandong Tianyunhe Information Technology Company Ltd., Zibo, China

Funder

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation

National Key Research and Development Program of China

Young Teacher Development Support Program of Shandong University of Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09737117.pdf?arnumber=9737117

Reference64 articles.

1. Building Change Detection for Remote Sensing Images Using a Dual-Task Constrained Deep Siamese Convolutional Network Model

2. Change Detection Based on Deep Siamese Convolutional Network for Optical Aerial Images

3. Fully convolutional Siamese networks for change detection;caye daudt;Proc 25th IEEE Int Conf Image Process (ICIP),2018

4. Detecting Urban Changes with Recurrent Neural Networks from Multitemporal Sentinel-2 Data

5. Efficient GAN-based remote sensing image change detection under noise conditions;huang;Proc Int Conf Image Process Capsule Netw,2020

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