101–120 von 122 Ergebnissen
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    Traffic Density Classification for Multiclass Vehicles Using Customized Convolutional Neural Network for Smart City

    Mane, Deepak / Bidwe, Ranjeet / Zope, Bhusan et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning , Convolutional neural network

    Obstacle Avoidance for an Autonomous Robot Car using Deep Learning ; En autonom robotbil undviker hinder med hjälp av djupinlärning

    Freier Zugriff
    Norén, Karl | BASE | 2019
    Schlagwörter: deep learning , convolutional neural network

    Hyper-parameters optimisation of deep CNN architecture for vehicle logo recognition

    Freier Zugriff
    Soon, Foo Chong / Khaw, Hui Ying / Chuah, Joon Huang et al. | IET | 2018
    Schlagwörter: deep convolutional neural network architecture , network convergence , feedforward neural nets , deep CNN architecture

      Hyper‐parameters optimisation of deep CNN architecture for vehicle logo recognition

      Freier Zugriff
      Soon, Foo Chong / Khaw, Hui Ying / Chuah, Joon Huang et al. | Wiley | 2018
      Schlagwörter: deep CNN architecture , deep convolutional neural network architecture , network convergence , feedforward neural nets

    Convolutional LSTM based transportation mode learning from raw GPS trajectories

    Freier Zugriff
    Nawaz, Asif / Zhiqiu, Huang / Senzhang, Wang et al. | Wiley | 2020
    Schlagwörter: convolution neural network , recurrent neural nets , deep learning‐based convolutional long short term memory model , convolutional neural nets , convolutional LSTM‐based transportation mode

    Transonic Wing Buffet Load Prediction at Structural Vibration Conditions

    Zahn, R. / Völkl, V. / Zieher, M. et al. | DataCite | 2023
    Schlagwörter: Long Short-Term Memory Neural Network (LSTM) , Deep Learning , Convolutional Autoencoder (CNN-AE)

    Deep Learning Approach to Detection of Preceding Vehicle in Advanced Driver Assistance

    Forczmański, Paweł / Nowosielski, Adam | Springer Verlag | 2016
    Schlagwörter: Deep learning , Convolutional neural network

    Space-Based Sensor Tasking Using Deep Reinforcement Learning

    Freier Zugriff
    Siew, Peng Mun / Jang, Daniel / Roberts, Thomas G. et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning , Convolutional neural network

    Deep-Learning Framework for Terminal Airspace Trajectory Prediction and In-Time Prognostics

    Sudarsanan, Varun S. / Kostiuk, Peter F. | AIAA | 2024
    Schlagwörter: Convolutional Neural Network , Deep Learning

    An analytic framework using deep learning for prediction of traffic accident injury severity based on contributing factors

    Ma, Zhengjing / Mei, Gang / Cuomo, Salvatore | Elsevier | 2021
    Schlagwörter: Deep learning , ANN , Artificial Neural Networks , Convolutional neural networks , Beep Neural Networks

    Robot-aided cloth classification using depth information and CNNs

    Freier Zugriff
    Gabas Nova, Antonio / Corona Puyane, Enric / Alenyà Ribas, Guillem et al. | BASE | 2016
    Schlagwörter: neural nets , deep convolutional neural network

    TrafficNN: CNN-Based Road Traffic Conditions Classification

    Shipu, Monjurur Kader / Mamun, Faisal Al / Razu, Shamim Hossen et al. | Springer Verlag | 2021
    Schlagwörter: Convolutional neural network , Deep learning

    Airport surface movement prediction and safety assessment with spatial–temporal graph convolutional neural network

    Zhang, Xiaoge / Zhong, Sanqiang / Mahadevan, Sankaran | Elsevier | 2022
    Schlagwörter: Spatial–Temporal Graph Convolutional Neural Network , Time-Extrapolator Convolution Neural Network , Graph Neural Network , Deep learning , Graph neural network

    Short‐term prediction of traffic flow under incident conditions using graph convolutional recurrent neural network and traffic simulation

    Freier Zugriff
    Fukuda, Shota / Uchida, Hideaki / Fujii, Hideki et al. | Wiley | 2020
    Schlagwörter: recurrent neural nets , neural nets , graph convolutional recurrent neural network , deep learning model

      Short-term prediction of traffic flow under incident conditions using graph convolutional recurrent neural network and traffic simulation

      Freier Zugriff
      Fukuda, Shota / Uchida, Hideaki / Fujii, Hideki et al. | IET | 2020
      Schlagwörter: deep learning model , graph convolutional recurrent neural network , neural nets , recurrent neural nets

    Depth estimation for advancing intelligent transport systems based on self-improving pyramid stereo network

    Freier Zugriff
    Tian, Yanling / Du, Yubo / Zhang, Qieshi et al. | IET | 2020
    Schlagwörter: deep learning model , pyramid stereo network , neural nets , convolutional neural networks

      Depth estimation for advancing intelligent transport systems based on self‐improving pyramid stereo network

      Freier Zugriff
      Tian, Yanling / Du, Yubo / Zhang, Qieshi et al. | Wiley | 2020
      Schlagwörter: neural nets , pyramid stereo network , deep learning model , convolutional neural networks

    A Novel Deep ConvNets Architecture for Traffic Sign Recognition

    Khyara, Hamza / Amine, Aouatif / Nassih, Bouchra | Springer Verlag | 2022
    Schlagwörter: Deep learning , Convolutional neural network (CNN)

    Hyperspectral Imaging for Non-destructive Testing of Composite Materials and Defect Classification

    Freier Zugriff
    Patil, Trunal / Pagano, Claudia / Marani, Roberto et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning , Convolutional neural network

    Smart parking sensors, technologies and applications for open parking lots: a review

    Freier Zugriff
    Paidi, Vijay / Fleyeh, Hasan / Håkansson, Johan et al. | IET | 2018
    Schlagwörter: feedforward neural nets , convolutional neural network , deep learning

      Smart parking sensors, technologies and applications for open parking lots: a review

      Freier Zugriff
      Paidi, Vijay / Fleyeh, Hasan / Håkansson, Johan et al. | Wiley | 2018
      Schlagwörter: convolutional neural network , deep learning , feedforward neural nets

    Real-time detection of distracted driving based on deep learning

    Freier Zugriff
    Tran, Duy / Manh Do, Ha / Sheng, Weihua et al. | IET | 2018
    Schlagwörter: deep convolutional neural networks , neural nets , deep learning , residual network

      Real‐time detection of distracted driving based on deep learning

      Freier Zugriff
      Tran, Duy / Manh Do, Ha / Sheng, Weihua et al. | Wiley | 2018
      Schlagwörter: residual network , neural nets , deep convolutional neural networks , deep learning

    Joint vehicle detection and distance prediction via monocular depth estimation

    Freier Zugriff
    Shen, Chao / Zhao, Xiangmo / Liu, Zhanwen et al. | IET | 2020
    Schlagwörter: convolutional neural nets , end-to-end deep convolutional neural network framework

      Joint vehicle detection and distance prediction via monocular depth estimation

      Freier Zugriff
      Shen, Chao / Zhao, Xiangmo / Liu, Zhanwen et al. | Wiley | 2020
      Schlagwörter: convolutional neural nets , end‐to‐end deep convolutional neural network framework

    Deep learning‐based helmet wear analysis of a motorcycle rider for intelligent surveillance system

    Freier Zugriff
    Yogameena, B. / Menaka, K. / Saravana Perumaal, S. | Wiley | 2019
    Schlagwörter: deep learning‐based helmet wear analysis , convolutional neural nets , region‐based convolutional neural network

      Deep learning-based helmet wear analysis of a motorcycle rider for intelligent surveillance system

      Freier Zugriff
      Yogameena, B. / Menaka, K. / Saravana Perumaal, S. | IET | 2019
      Schlagwörter: convolutional neural nets , region-based convolutional neural network , deep learning-based helmet wear analysis