U-MGA: A Multi-Module Unet Optimized with Multi-Scale Global Attention Mechanisms for Fine-Grained S...
U-MGA: A Multi-Module Unet Optimized with Multi-Scale Global Attention Mechanisms for Fine-Grained Segmentation of Cultivated Areas
About this item
Full title
Author / Creator
Chen, Yun , Xie, Yiheng , Yao, Weiyuan , Zhang, Yu , Wang, Xinhong , Yang, Yanli and Tang, Lingli
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
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More information
Scope and Contents
Contents
Arable land is fundamental to agricultural production and a crucial component of ecosystems. However, its complex texture and distribution in remote sensing images make it susceptible to interference from other land cover types, such as water bodies, roads, and buildings, complicating accurate identification. Building on previous research, this stu...
Alternative Titles
Full title
U-MGA: A Multi-Module Unet Optimized with Multi-Scale Global Attention Mechanisms for Fine-Grained Segmentation of Cultivated Areas
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_922b991054364aedb4e40557a04e58a8
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_922b991054364aedb4e40557a04e58a8
Other Identifiers
ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs17050760
