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  • Forest restoration is more ... Forest restoration is more than firing seeds from a drone
    Castro, Jorge; Morales‐Rueda, Fernando; Alcaraz‐Segura, Domingo ... Restoration ecology, January 2023, 2023-01-00, 20230101, Volume: 31, Issue: 1
    Journal Article
    Peer reviewed
    Open access

    We are witnessing a rapid increase in news sending the message that drone seeding is a promising technological solution to implement forest restoration at large spatial scales. However, there are ...
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32.
  • Classifying the content of ... Classifying the content of social media images to support cultural ecosystem service assessments using deep learning models
    Cardoso, Ana Sofia; Renna, Francesco; Moreno-Llorca, Ricardo ... Ecosystem services, April 2022, 2022-04-00, Volume: 54
    Journal Article
    Peer reviewed

    •We used freely available deep learning models to analyse social media content in two distinct Iberian areas.•Our models allowed accurate classification of nature attributes underlying cultural ...
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  • Deep recurrent neural netwo... Deep recurrent neural network for geographical entities disambiguation on social media data
    Zuheros, Cristina; Tabik, Siham; Valdivia, Ana ... Knowledge-based systems, 06/2019, Volume: 173
    Journal Article
    Peer reviewed

    A particular challenge in Natural Language Processing is the disambiguation of polysemic words. The great availability, diversity and the speed of changing of the data from on-line sources force the ...
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  • Automated precise seeding w... Automated precise seeding with drones and artificial intelligence: a workflow
    Castro, Jorge; Alcaraz‐Segura, Domingo; Baltzer, Jennifer L. ... Restoration ecology, July 2024, Volume: 32, Issue: 5
    Journal Article
    Peer reviewed
    Open access

    Aerial seeding with drones has great potential in forest restoration but faces enormous challenges to be efficient and scalable. Current protocols use blanket seeding throughout the area to be ...
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  • Can citizen science and soc... Can citizen science and social media images support the detection of new invasion sites? A deep learning test case with Cortaderia selloana
    Cardoso, Ana Sofia; Malta-Pinto, Eva; Tabik, Siham ... Ecological informatics, July 2024, 2024-07-00, Volume: 81
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    Open access

    Deep learning has advanced the content analysis of digital data, unlocking opportunities for detecting, mapping, and monitoring invasive species. Here, we tested the ability of open source ...
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  • MNIST-NET10: A heterogeneou... MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1% error rate. Ensembles overview and proposal
    Tabik, Siham; Alvear-Sandoval, Ricardo F.; Ruiz, María M. ... Information fusion, October 2020, 2020-10-00, Volume: 62
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    •It provides an overview of the most popular ensemble methods.•It analyzes several fusion schemes using MNIST as guiding thread.•It introduces MNIST-NET10, a complex heterogeneous fusion ...
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  • Climate legacies drive the distribution and future restoration potential of dryland forests
    Guirado, Emilio; Delgado-Baquerizo, Manuel; Martínez-Valderrama, Jaime ... Nature plants, 08/2022, Volume: 8, Issue: 8
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    Knowing the extent and environmental drivers of forests is key to successfully restore degraded ecosystems, and to mitigate climate change and desertification impacts using tree planting. Water ...
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  • Demystifying the 16 × 16 th... Demystifying the 16 × 16 thread-block for stencils on the GPU
    Tabik, Siham; Peemen, Maurice; Guil, Nicolas ... Concurrency and computation, 25 December 2015, Volume: 27, Issue: 18
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    Summary Stencil computation is of paramount importance in many fields, in image processing, structural biology and biomedicine, among others. There exists a permanent demand of maximizing the ...
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  • TimeSpec4LULC: a global mul... TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning
    Khaldi, Rohaifa; Alcaraz-Segura, Domingo; Guirado, Emilio ... Earth system science data, 03/2022, Volume: 14, Issue: 3
    Journal Article
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    Land use and land cover (LULC) mapping are of paramount importance to monitor and understand the structure and dynamics of the Earth system. One of the most promising ways to create accurate global ...
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