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Mamba-RSI: a state-space deep learning framework for efficient land-use and land-cover classification in remote sensing imagery.

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Title: Mamba-RSI: a state-space deep learning framework for efficient land-use and land-cover classification in remote sensing imagery.
Authors: Abdelbaki, Wiem1 (AUTHOR), Bouchelligua, Wided2 (AUTHOR), Nasir, Inzamam Mashood3 (AUTHOR) inzamam.nasir@mruni.eu, Tehsin, Sara4 (AUTHOR), Alshaya, Hend2 (AUTHOR)
Source: AIMS Mathematics. 2026, Vol. 11 Issue 3, p1-48. 48p.
Database: Mathematics Source
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Header DbId: msf
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Mamba-RSI: a state-space deep learning framework for efficient land-use and land-cover classification in remote sensing imagery.
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  Data: <searchLink fieldCode="JN" term="%22AIMS+Mathematics%22">AIMS Mathematics</searchLink>. 2026, Vol. 11 Issue 3, p1-48. 48p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=msf&AN=192838910
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      – Code: eng
        Text: English
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      – TitleFull: Mamba-RSI: a state-space deep learning framework for efficient land-use and land-cover classification in remote sensing imagery.
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            NameFull: Nasir, Inzamam Mashood
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              Text: 2026
              Type: published
              Y: 2026
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