PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-r...
PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing
About this item
Full title
Author / Creator
Zhang, Ziwen , Liu, Qi , Liu, Xiaodong , Zhang, Yonghong , Du, Zihao and Cao, Xuefei
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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More information
Scope and Contents
Contents
In the field of remote sensing image interpretation, automatically extracting water body information from high-resolution images is a key task. However, facing the complex multi-scale features in high-resolution remote sensing images, traditional methods and basic deep convolutional neural networks are difficult to effectively capture the global sp...
Alternative Titles
Full title
PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_a697eec1542e459b835d120a52e1b049
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a697eec1542e459b835d120a52e1b049
Other Identifiers
ISSN
2192-113X
E-ISSN
2192-113X
DOI
10.1186/s13677-024-00637-5
