Showing 1,221 - 1,240 results of 21,342 for search '(( significant decrease decrease ) OR ( significant ((green decrease) OR (greater decrease)) ))*', query time: 0.60s Refine Results
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    Seasonal spatial-temporal trend of NDVI of burned forested areas in Africa (2001–2020). by Oswaldo Maillard (20660661)

    Published 2025
    “…<p>Areas with increasing (green) or decreasing (red) vegetation, based on the Mann-Kendall test and statistically significance values (<i>p</i> < 0.05) for DJF (December-February), MAM (March-May), JJA (June-August) and SON (September-November). …”
  5. 1225

    Seasonal spatial-temporal trend of NDVI in burned areas across Africa (2001–2020). by Oswaldo Maillard (20660661)

    Published 2025
    “…<p>Areas with increasing (green) or decreasing (red) vegetation, based on the Mann-Kendall test and statistically significance values (<i>p</i> < 0.05) for DJF (December-February), MAM (March-May), JJA (June-August), and SON (September-November). …”
  6. 1226

    S1 File - by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
  7. 1227

    Seasonal spatial-temporal trend of NDVI of burned forested areas in Africa (2001–2020) by countries and territories. by Oswaldo Maillard (20660661)

    Published 2025
    “…<p>Areas with increasing (green) or decreasing (red) vegetation, based on the Mann-Kendall test and statistically significance values (<i>p</i> < 0.05) for December-February (DJF), March-May (MAM), June-August (JJA) and September-November (SON). …”
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    Confusion matrix for ClinicalBERT model. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
  9. 1229

    Confusion matrix for LastBERT model. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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    Student model architecture. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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    Configuration of the LastBERT model. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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    Confusion matrix for DistilBERT model. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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    ROC curve for LastBERT model. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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    Sample Posts from the ADHD dataset. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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    Top-level overview for ADHD classification study. by Ahmed Akib Jawad Karim (20427740)

    Published 2025
    “…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
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