Treffer 1 - 9 von 9 für Suche 'Benhammou, Yassir', Suchdauer: 0,54s Treffer weiter einschränken
  1. 1
    Sentinel2GlobalLULC: A Sentinel-2 RGB image tile dataset for global land use/cover mapping with deep learning

    Sentinel2GlobalLULC: A Sentinel-2 RGB image tile dataset for global land use/cover mapping with deep learning von Benhammou, Yassir, Alcaraz-Segura, Domingo, Guirado, Emilio, Khaldi, Rohaifa, Achchab, Boujemâa, Herrera, Francisco, Tabik, Siham

    Veröffentlicht in Scientific data

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  2. 2
    CI-Dataset and DetDSCI Methodology for Detecting Too Small and Too Large Critical Infrastructures in Satellite Images: Airports and Electrical Substations as Case Study

    CI-Dataset and DetDSCI Methodology for Detecting Too Small and Too Large Critical Infrastructures in Satellite Images: Airports and Electrical Substations as Case Study von Perez-Hernandez, Francisco, Rodriguez-Ortega, Jose, Benhammou, Yassir, Herrera, Francisco, Tabik, Siham


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  3. 3
    BreakHis based breast cancer automatic diagnosis using deep learning: Taxonomy, survey and insights

    BreakHis based breast cancer automatic diagnosis using deep learning: Taxonomy, survey and insights von Benhammou, Yassir, Achchab, Boujemâa, Herrera, Francisco, Tabik, Siham

    Veröffentlicht in Neurocomputing (Amsterdam)

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  4. 4
    TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning

    TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning von Khaldi, Rohaifa, Alcaraz-Segura, Domingo, Guirado, Emilio, Benhammou, Yassir, El Afia, Abdellatif, Herrera, Francisco, Tabik, Siham

    Veröffentlicht in Earth system science data

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  5. 5
    AndalUnmixingRGB: A dataset of Sentinel-2 Digital RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0)

    AndalUnmixingRGB: A dataset of Sentinel-2 Digital RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unm... von Benhammou, Yassir Benhammou, Rodríguez-Ortega, José Rodríguez-Ortega, Alcaraz-Segura, Domingo Alcaraz-Segura, Tabik, Siham Tabik

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  6. 6
    CI-dataset and DetDSCI methodology for detecting too small and too large critical infrastructures in satellite images: Airports and electrical substations as case study

    CI-dataset and DetDSCI methodology for detecting too small and too large critical infrastructures in satellite images: Airports and electrical substations as case study von Pérez-Hernández, Francisco, Rodríguez-Ortega, José, Benhammou, Yassir, Herrera, Francisco, Tabik, Siham

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  7. 7
    Sentinel2GlobalLULC: A dataset of Sentinel-2 georeferenced RGB imagery annotated for global land use/land cover mapping with deep learning (License CC BY 4.0)

    Sentinel2GlobalLULC: A dataset of Sentinel-2 georeferenced RGB imagery annotated for global land use/land cover mapping with deep learning (License CC BY 4.0) von Benhammou, Yassir, Alcaraz-Segura, Domingo, Guirado, Emilio, Khaldi, Rohaifa, Tabik, Siham

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  8. 8
    TimeSpec4LULC: A Smart-Global Dataset of Multi-Spectral Time Series of MODIS Terra-Aqua from 2000 to 2021 for Training Machine Learning models to perform LULC Mapping

    TimeSpec4LULC: A Smart-Global Dataset of Multi-Spectral Time Series of MODIS Terra-Aqua from 2000 to 2021 for Training Machine Learning models to perform LULC Mapping von Khaldi, Rohaifa, Alcaraz-Segura, Domingo, Guirado, Emilio, Benhammou, Yassir, Tabik, Siham

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  9. 9
    CI-dataset and DetDSCI methodology for detecting too small and too large critical infrastructures in satellite images: Airports and electrical substations as case study

    CI-dataset and DetDSCI methodology for detecting too small and too large critical infrastructures in satellite images: Airports and electrical substations as case study von Pérez-Hernández, Francisco, Rodríguez-Ortega, José, Benhammou, Yassir, Herrera, Francisco, Tabik, Siham

    Veröffentlicht in arXiv.org

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