1–20 von 21 Ergebnissen
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    Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification

    Freier Zugriff
    Shi, Zengshu / Du, Yiman / Yao, Xinwen | Wiley | 2023
    Schlagwörter: improved deep convolutional neural network

    Using spatio‐temporal deep learning for forecasting demand and supply‐demand gap in ride‐hailing system with anonymised spatial adjacency information

    Freier Zugriff
    Rahman, Md. Hishamur / Rifaat, Shakil Mohammad | Wiley | 2021
    Schlagwörter: Neural nets , convolutional neural network , deep learning , recurrent neural network

    Multi‐graph convolutional network for short‐term passenger flow forecasting in urban rail transit

    Freier Zugriff
    Zhang, Jinlei / Chen, Feng / Guo, Yinan et al. | Wiley | 2020
    Schlagwörter: multigraph convolutional network , deep‐learning technologies , graph convolutional network , three‐dimensional convolutional neural network , convolutional 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

    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

    Deep learning‐based real‐time fine‐grained pedestrian recognition using stream processing

    Freier Zugriff
    Zhang, Weishan / Wang, Zhichao / Liu, Xin et al. | Wiley | 2018
    Schlagwörter: deep learning‐based real‐time fine‐grained pedestrian recognition , neural nets , improved single‐shot detector , improved convolutional neural network

    Automated visual inspection of target parts for train safety based on deep learning

    Freier Zugriff
    Zhou, Fuqiang / Song, Ya / Liu, Liu et al. | Wiley | 2018
    Schlagwörter: composite neural network , neural nets , stacked auto‐encoder convolutional neural network , deep learning

    Lateral distance detection model based on convolutional neural network

    Freier Zugriff
    Zhang, Xiang / Yang, Wei / Tang, Xiaolin et al. | Wiley | 2019
    Schlagwörter: improved image quilting algorithm , neural nets , convolutional neural network , deep learning model

    Innovative method for traffic data imputation based on convolutional neural network

    Freier Zugriff
    Zhuang, Yifan / Ke, Ruimin / Wang, Yinhai | Wiley | 2019
    Schlagwörter: convolutional neural network , deep‐learning method , feedforward neural nets

    Extensive exploration of comprehensive vehicle attributes using D‐CNN with weighted multi‐attribute strategy

    Freier Zugriff
    Yan, Zhuo / Feng, Youji / Cheng, Cheng et al. | Wiley | 2018
    Schlagwörter: deep convolutional neural network , feedforward neural nets

    Vision‐based vehicle behaviour analysis: a structured learning approach via convolutional neural networks

    Freier Zugriff
    Mou, Luntian / Xie, Haitao / Mao, Shasha et al. | Wiley | 2020
    Schlagwörter: structured convolutional neural networks model , overfitting‐preventing deep neural network , convolutional neural nets

    Deep learning‐based vehicle detection with synthetic image data

    Freier Zugriff
    Wang, Ye / Deng, Weiwen / Liu, Zhenyi et al. | Wiley | 2019
    Schlagwörter: convolutional neural network‐based object detectors , deep learning‐based vehicle detection , neural nets

    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

    Driver identification using 1D convolutional neural networks with vehicular CAN signals

    Freier Zugriff
    Hu, Hongyu / Liu, Jiarui / Gao, Zhenhai et al. | Wiley | 2020
    Schlagwörter: vehicular controller area network bus signals , 1D convolutional neural networks , deep learning framework , convolutional neural nets , one‐dimensional convolutional neural network , convolutional‐pooling layers

    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

    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

    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

    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

    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. | Wiley | 2020
    Schlagwörter: convolutional neural nets , end‐to‐end deep convolutional neural network framework