Attentional Dense Convolutional Neural Network for Water Body Extraction From Sentinel-2 Images-Reference-Cited by-同舟云学术

Attentional Dense Convolutional Neural Network for Water Body Extraction From Sentinel-2 Images

Published:2022 Issue: Volume:15 Page:6804-6816
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Parajuli Janak¹,Fernandez-Beltran Ruben²^ORCID,Kang Jian³^ORCID,Pla Filiberto¹^ORCID

Affiliation:

1. Department of Computer Languages and Systems, Institute of New Imaging Technologies, University Jaume I, Castellón de la Plana, Spain

2. Department of Computer Science and Systems, University of Murcia, Murcia, Spain

3. School of Electronic and Information Engineering Department of Electronic Science and Technology, Soochow University, Suzhou, China

Funder

Ministerio de Ciencia e Innovación

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

Reference55 articles.

1. Extracting urban water by combining deep learning and Google Earth Engine;wang;IEEE J Sel Top Appl Earth Obs Remote Sens,2020

2. Deep learning for extracting water body from Landsat imagery;yang;Int J Innov Comput Inf Control,2015

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