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  1. 681

    A New Video-Based Crash Detection Method: Balancing Speed and Accuracy Using a Feature Fusion Deep Learning Framework by Zhenbo Lu, Wei Zhou, Shixiang Zhang, Chen Wang

    Published 2020-01-01
    “…The proposed model was trained by a set of video clips covering 330 crash and 342 noncrash events. In general, the proposed model achieved an accuracy of 87.78% on the testing dataset and an acceptable detection speed (FPS > 30 with GTX 1060). …”
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    Transformer-Based Amharic-to-English Machine Translation With Character Embedding and Combined Regularization Techniques by Surafiel Habib Asefa, Yaregal Assabie

    Published 2025-01-01
    “…The primary challenges include the scarcity of parallel data, which increases the risk of overfitting and limits the model’s ability to generalize effectively, and the complex morphology of Amharic, which further complicates learning patterns in translation tasks. …”
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  10. 690

    Surveying Nearshore Bathymetry Using Multispectral and Hyperspectral Satellite Imagery and Machine Learning by David Hartmann, Mathieu Gravey, Timothy David Price, Wiebe Nijland, Steven Michael de Jong

    Published 2025-01-01
    “…Future studies are recommended to train neural networks with images from various regions to increase generalization and method portability. Models are preferably trained by area-segregated splits to ensure independence between the training and testing set. …”
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  11. 691

    Numerical Simulation of Surface Energy and Water Balances over a Semiarid Grassland Ecosystem in the West African Savanna by Emmanuel Quansah, Genki Katata, Matthias Mauder, Thompson Annor, Leonard K. Amekudzi, Jan Bliefernicht, Dominikus Heinzeller, Ahmed A. Balogun, Harald Kunstmann

    Published 2017-01-01
    “…The results showed that the model overall reproduced the diurnal changes in the observed energy fluxes, especially the net radiation (Rn), compared to half-hourly eddy covariance flux measurements, for the study periods. …”
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  12. 692

    A Novel Network for Choroidal Segmentation Based on Enhanced Boundary Information by Wenbo Huang, Chaofan Qu, Yang Yan

    Published 2025-01-01
    “…To address these issues, this paper proposes an automatic choroid segmentation network, termed Boundary Enhancement Net (BENet), which enhances boundary information to facilitate precise recognition and achieve end-to-end automatic segmentation. …”
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