Deforestation Detection Based on U-Net and LSTM in Optical Satellite Remote Sensing Images-Reference-Cited by-同舟云学术

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Deforestation Detection Based on U-Net and LSTM in Optical Satellite Remote Sensing Images

Published:2021-07-11 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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Author:

Zhang Jie,Wang Zhibao,Bai Lu,Song Guangfu,Tao Jinhua,Chen Liangfu

Funder

TUOHAI special project 2020 from Bohai Rim Energy Research Institute of Northeast Petroleum University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9553015/9553016/09554689.pdf?arnumber=9554689

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2. A Critical Examination of SAR Colorization Impact on Flood Mapping Accuracy;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

3. Comparative Analysis of Modern Methods for Surface Type Identification in RGB Image Data;2024 Zooming Innovation in Consumer Technologies Conference (ZINC);2024-05-22

4. Deforestation rate estimation using crossbreed multilayer convolutional neural networks;Multimedia Tools and Applications;2024-05-13

5. A Deep Learning Based Platform for Remote Sensing Images Change Detection Integrating Crowdsourcing and Active Learning;Sensors;2024-02-26

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