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    ⋆This paper has been handled by associate editor Tony Sze.The application of novel connected vehicles emulated data on real-time crash potential prediction for arterials

    Li, Pei / Abdel-Aty, Mohamed / Cai, Qing et al. | Elsevier | 2020
    Schlagwörter: Deep learning

    2D-supervised fast neural fluid reconstruction technique for time-resolved volumetric flame reconstruction

    Zhang, Fuhao / Zhang, Weixuan / Gong, Shuicheng et al. | Elsevier | 2023
    Schlagwörter: Deep learning

    3D CNNs on distance matrices for human action recognition

    Freier Zugriff
    Hernández Ruiz, Alejandro José / Porzi, Lorenzo / Rota Bulò, Samuel et al. | BASE | 2017
    Schlagwörter: deep learning

    3D vehicle detection on an FPGA from LiDAR point clouds

    Freier Zugriff
    García López, Javier / Moreno-Noguer, Francesc / Agudo, Antonio | BASE | 2019
    Schlagwörter: Deep learning

    3D Visualization of MPC-based Algorithms for Autonomous Vehicles

    Freier Zugriff
    Sörliden, Pär | BASE | 2019
    Schlagwörter: deep learning

    3D YOLO: End-to-End 3D Object Detection Using Point Clouds ; 3D YOLO: Objektdetektering i 3D med LiDAR-data

    Freier Zugriff
    Al Hakim, Ezeddin | BASE | 2018
    Schlagwörter: Deep Learning

    4D flight trajectory prediction using a hybrid Deep Learning prediction method based on ADS-B technology: A case study of Hartsfield–Jackson Atlanta International Airport (ATL)

    Shafienya, Hesam / Regan, Amelia C. | Elsevier | 2022
    Schlagwörter: Deep learning

    A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models

    Sengupta, Agnimitra / Mondal, Sudeepta / Das, Adway et al. | Elsevier | 2024
    Schlagwörter: Deep learning

    A Bayesian deep learning method for freeway incident detection with uncertainty quantification

    Liu, Genwang / Jin, Haolin / Li, Jiaze et al. | Elsevier | 2022
    Schlagwörter: Bayesian deep learning

    Accident Detection in Surveillance Camera

    Adil, A. P. / Anandhu, M. G. / Joy, Jeovan Elsa et al. | Springer Verlag | 2023
    Schlagwörter: Deep learning

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