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    Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data by Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali

    Published 2025-01-01
    “…Initially, we apply a deep convolutional neural network (CNN) to a specialized mineral dataset to map mineral deposits within the study area. …”
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  3. 4643

    Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

    Published 2025-03-01
    “…First, NASA’s Fire Information for Resource Management System (FIRMS) dataset spanning +20 years is processed using a spatio-temporal clustering algorithm to create refined wildfire datasets. …”
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    Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study by Lambert, Charlotte, Virgili, Auriane

    Published 2023-04-01
    “…We provided clear evidence of stochasticity in the modelling process (particularly in the shapes of relationships): two dataset from the same survey, species and region could yield different results. …”
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    Measurements of groundwater, hydrodynamics, and sand characteristics at a dissipative sea turtle nesting beach by Jakob C. Christiaanse, José A. A. Antolínez, Meye J. van der Grinten, Falco Taal, Jens Figlus, Timothy M. Dellapenna, Benjamin Ritt, Christopher D. Marshall, Peter A. Tereszkiewicz, Nicholas Cohn, Edward J. Majzlik, Ad J. H. M. Reniers

    Published 2025-01-01
    “…Other collected data include bathymetry and topography surveys, subsurface temperature and moisture content readings, and sediment characteristics. This comprehensive dataset can be used to (1) study relevant beach inundation and groundwater processes, including their effect on the local ecosystem (e.g., repeated flooding of sea turtle nests), (2) study the propagation of nearshore hydrodynamic processes into the beach matrix and groundwater table, and (3) validate existing beach groundwater models.…”
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    Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation. by Ahmed Akib Jawad Karim, Kazi Hafiz Md Asad, Md Golam Rabiul Alam

    Published 2025-01-01
    “…The model was also used on a real-world ADHD dataset with an accuracy of 85%, F1 score of 85%, precision of 85%, and recall of 85%. …”
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    PSiamRML: Target Recognition and Matching Integrated Localization Algorithm Based on Pseudo-Siamese Network by Jiwei Fan, Xiaogang Yang, Ruitao Lu, Xueli Xie, Siyu Wang

    Published 2023-01-01
    “…The University-Release dataset was used to compare and analyze the performance of the proposed algorithm to verify its superiority and feasibility. …”
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  10. 4650

    Incremental Instance-Oriented 3D Semantic Mapping via RGB-D Cameras for Unknown Indoor Scene by Wei Li, Junhua Gu, Benwen Chen, Jungong Han

    Published 2020-01-01
    “…We evaluate our system on different indoor scenes including offices, bedrooms, and living rooms from the SceneNN dataset, and the results show that our method not only builds the instance-oriented semantic map efficiently but also enhances the accuracy of the individual instance in the scene.…”
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    A pooled analysis of the side effects of non-invasive Transcutaneous Auricular Vagus Nerve Stimulation (taVNS) by Manon Giraudier, Carlos Ventura-Bort, Christoph Szeska, Mathias Weymar, Mathias Weymar

    Published 2025-02-01
    “…While previous research highlights its efficacy, the safety profile of taVNS has been less extensively examined.MethodsThis study therefore aimed to systematically investigate side effects of taVNS in a large pooled dataset consisting of n = 488 participants, utilizing a standardized questionnaire to assess ten reported side effects. …”
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    Forest stand height predicted from ICESat-2 ATLAS data for forest inventory and comparison to airborne laser scanning metrics by Lang Mait, Tampuu Tauri, Trofimov Heido

    Published 2024-12-01
    “…The study analysed 2019–2022 summertime canopy height predictions (HICESat) given in ICESat-2 ATLAS dataset ATL08 for hemiboreal forests growing on an area of 40,000 km2 in Estonia around 25.6° E, 58.8° N. …”
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