41–60 von 109 Ergebnissen
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    Real-time driving risk assessment using deep learning with XGBoost

    Shi, Liang / Qian, Chen / Guo, Feng | Elsevier | 2022
    Schlagwörter: Deep learning , Convolutional neural network

    Shrinkage Crack Detection in Expansive Soil using Deep Convolutional Neural Network and Transfer Learning

    Andrushia, A. Diana / Neebha, T. Mary / Umadevi, S. et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning , Deep convolutional neural network

    Deep Learning-Based Real-Time Crack Segmentation for Pavement Images

    Wang, Wenjun / Su, Chao | Springer Verlag | 2021
    Schlagwörter: Deep learning , Convolutional neural network

    A data-driven traffic modeling for analyzing the impacts of a freight departure time shift policy

    Nadi, Ali / Sharma, Salil / van Lint, J.W.C. et al. | Elsevier | 2022
    Schlagwörter: Graph convolutional deep neural network

    Analyzing the opening and closing of windows in residential for predicting the energy consumption using optimized multi-scale convolution networks

    Sivapriya, C. / Subbaiyan, G. | Emerald Group Publishing | 2024
    Schlagwörter: One-dimensional deep convolutional neural network , Deep temporal context network

    A Damage Localization Approach for Rahmen Bridge Based on Convolutional Neural Network

    Lee, Kanghyeok / Byun, Namju / Shin, Do Hyoung | Springer Verlag | 2020
    Schlagwörter: Convolutional neural network , Deep learning

    Short-term FFBS demand prediction with multi-source data in a hybrid deep learning framework

    Freier Zugriff
    Bao, Jie / Yu, Hao / Wu, Jiaming | IET | 2019
    Schlagwörter: convolutional neural nets , hybrid deep learning framework , artificial neural network , hybrid deep learning neural network , convolutional neural network , deep learning approach , recurrent neural nets

      Short‐term FFBS demand prediction with multi‐source data in a hybrid deep learning framework

      Freier Zugriff
      Bao, Jie / Yu, Hao / Wu, Jiaming | Wiley | 2019
      Schlagwörter: hybrid deep learning neural network , convolutional neural network , convolutional neural nets , deep learning approach , artificial neural network , recurrent neural nets , hybrid deep learning framework

    AI-based movement planning for autonomous and teleoperated vehicles including the development of a simulation environment an intelligent agent

    Freier Zugriff
    Thomas Nützel | BASE | 2018
    Schlagwörter: Neural Network , Deep Learning , Convolutional Neural Network

    Development of Real-Time Unmanned Aerial Vehicle Urban Object Detection System with Federated Learning

    Lu, You-Ru / Sun, Dengfeng | AIAA | 2024
    Schlagwörter: Deep Convolutional Neural Network

    Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

    Feng, Chuncheng / Zhang, Hua / Wang, Shuang et al. | Springer Verlag | 2019
    Schlagwörter: deep convolutional neural network

    Convolutional Neural Networks for Flexible Payload Management in VHTS Systems

    Freier Zugriff
    Ortiz-Gomez, Flor G. / Tarchi, Daniele / Martinez, Ramon et al. | BASE | 2021
    Schlagwörter: convolutional neural network (CNN) , deep learning (DL)

    Object detection and recognition with event driven cameras

    Freier Zugriff
    IACONO, MASSIMILIANO | BASE | 2020
    Schlagwörter: deep learning , spiking neural network , convolutional neural network

    Wire Databases Generation Using Deep Learning Methods for Rotorcraft Wire Strike Prevention

    Achour, Gabriel / Harris, Caleb / Payan, Alexia P. et al. | AIAA | 2024
    Schlagwörter: Deep Learning , Convolutional Neural Network , Pole Locations and Wire Network Prediction

    DQN-Based Deep Reinforcement Learning for Autonomous Driving

    Pérez-Gil, Óscar / Barea, Rafael / López-Guillén, Elena et al. | Springer Verlag | 2020
    Schlagwörter: Convolutional neural network , Deep q-network agent

    Fatigue driving recognition network: fatigue driving recognition via convolutional neural network and long short‐term memory units

    Freier Zugriff
    Xiao, Zhitao / Hu, Zhiqiang / Geng, Lei et al. | Wiley | 2019
    Schlagwörter: deep convolutional layers , neural nets , fatigue driving recognition network , end‐to‐end trainable convolutional neural network , deep cascaded multitask framework

      Fatigue driving recognition network: fatigue driving recognition via convolutional neural network and long short-term memory units

      Freier Zugriff
      Xiao, Zhitao / Hu, Zhiqiang / Geng, Lei et al. | IET | 2019
      Schlagwörter: deep convolutional layers , fatigue driving recognition network , end-to-end trainable convolutional neural network , neural nets , deep cascaded multitask framework

    Autonomous Driving Through Road Segmentation Based on Computer Vision Techniques

    Jain, Aditi / Harper, Matthew / Jayabalan, Manoj et al. | Springer Verlag | 2023
    Schlagwörter: Deep convolutional neural network , Fully convolutional network

    Heat Flux Prediction of Radiation Balance Wall by Deep Convolutional Neural Networks

    Dai, Gang / Zhao, Wenwen / Yao, Shaobo et al. | AIAA | 2024
    Schlagwörter: Deep Convolutional Neural Network

    Prediction of wing buffet pressure loads using a convolutional and recurrent neural network framework

    Freier Zugriff
    Zahn, R. / Weiner, A. / Breitsamter, C. | Springer Verlag | 2024
    Schlagwörter: Deep learning , Convolutional autoencoder , Long short-term memory neural network

    Image-Based Meta-Reinforcement Learning for Autonomous Guidance of an Asteroid Impactor

    Federici, Lorenzo / Scorsoglio, Andrea / Ghilardi, Luca et al. | AIAA | 2022
    Schlagwörter: Deep Convolutional Neural Network

    Scale-aware limited deformable convolutional neural networks for traffic sign detection and classification

    Freier Zugriff
    Liu, Zhanwen / Shen, Chao / Fan, Xing et al. | IET | 2020
    Schlagwörter: scale-aware multitask region proposal network module , neural nets , deformable convolutional neural networks , region-based deep convolutional neural network framework