Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape imag...
Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis
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Publisher
United States: Public Library of Science
Journal title
Language
English
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Publisher
United States: Public Library of Science
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Scope and Contents
Contents
Semantic segmentation of cityscapes via deep learning is an essential and game-changing research topic that offers a more nuanced comprehension of urban landscapes. Deep learning techniques tackle urban complexity and diversity, which unlocks a broad range of applications. These include urban planning, transportation management, autonomous driving,...
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Full title
Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis
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TN_cdi_doaj_primary_oai_doaj_org_article_268e54d2b3c840228b4f0f855ecf21a4
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_268e54d2b3c840228b4f0f855ecf21a4
Other Identifiers
ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0300767
