Landslide Recognition from Multi-Feature Remote Sensing Data Based on Improved Transformers
Landslide Recognition from Multi-Feature Remote Sensing Data Based on Improved Transformers
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Contents
Efficient and accurate landslide recognition is crucial for disaster prevention and post-disaster rescue efforts. However, compared to machine learning, deep learning approaches currently face challenges such as long model runtimes and inefficiency. To tackle these challenges, we proposed a novel knowledge distillation network based on Swin-Transfo...
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Full title
Landslide Recognition from Multi-Feature Remote Sensing Data Based on Improved Transformers
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Author / Creator
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TN_cdi_doaj_primary_oai_doaj_org_article_d059e3c22217453abaea89072024338d
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d059e3c22217453abaea89072024338d
Other Identifiers
ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs15133340
