LWCDNet: A Lightweight Fully Convolution Network for Change Detection in Optical Remote Sensing Imagery-Reference-Cited by-同舟云学术

LWCDNet: A Lightweight Fully Convolution Network for Change Detection in Optical Remote Sensing Imagery

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Han Min¹^ORCID,Li Ran²^ORCID,Zhang Chengkun³^ORCID

Affiliation:

1. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Liaoning, China

2. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China

3. Department of Computer Technology and Application, Qinghai University, Xining, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09734020.pdf?arnumber=9734020

Reference16 articles.

1. Land-Use/Land-Cover change detection based on a Siamese global learning framework for high spatial resolution remote sensing imagery

2. The lovasz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks;berman;Proc IEEE Conf Comput Vis Pattern Recognit,2018

3. A spatial-temporal attention-based method and a new dataset for remote sensing image change detection;chen;Remote Sens,2020

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

5. Multitask learning for large-scale semantic change detection;daudt;Comput Vis Image Understand,2019

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