Synonyme wurden verwendet für: learning  deep learning
Suche ohne Synonyme: keywords:( deep learning)

1–20 von 53 Ergebnissen
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    Vision-based vehicle behaviour analysis: a structured learning approach via convolutional neural networks

    Freier Zugriff
    Mou, Luntian / Xie, Haitao / Mao, Shasha et al. | IET | 2020
    Schlagwörter: structured learning approach , multitask learning , learning (artificial intelligence) , transfer learning , overfitting-preventing deep neural network

    Value-based deep reinforcement learning for adaptive isolated intersection signal control

    Freier Zugriff
    Wan, Chia-Hao / Hwang, Ming-Chorng | IET | 2018
    Schlagwörter: machine learning-based framework , learning (artificial intelligence) , deep Q-learning neural network , value-based deep reinforcement learning

    Traffic light control using deep policy-gradient and value-function-based reinforcement learning

    Freier Zugriff
    Mousavi, Seyed Sajad / Schukat, Michael / Howley, Enda | IET | 2017
    Schlagwörter: deep policy-gradient RL algorithm , learning (artificial intelligence) , deep neural network architectures , value-function-based reinforcement learning

    Three-stage RGBD architecture for vehicle and pedestrian detection using convolutional neural networks and stereo vision

    Freier Zugriff
    Ferraz, Pedro Augusto Pinho / de Oliveira, Bernardo Augusto Godinho / Ferreira, Flávia Magalhães Freitas et al. | IET | 2020
    Schlagwörter: residual learning , learning (artificial intelligence) , deep learning , transfer learning

    Spatio-temporal expand-and-squeeze networks for crowd flow prediction in metropolis

    Freier Zugriff
    Yang, Bing / Kang, Yan / Li, Hao et al. | IET | 2020
    Schlagwörter: learning (artificial intelligence) , deep learning methods

    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: learning (artificial intelligence) , deep learning

    Short-term traffic flow prediction of road network based on deep learning

    Freier Zugriff
    Han, Lei / Huang, Yi-Shao | IET | 2020
    Schlagwörter: learning (artificial intelligence) , deep belief network model , deep learning , kernel extreme learning machine classifier

    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: machine-learning-based traffic prediction , model learning , deep learning model , learning (artificial intelligence)

    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: hybrid deep learning framework , learning (artificial intelligence) , hybrid deep learning neural network , deep learning approach

    Semi-supervised double duelling broad reinforcement learning in support of traffic service in smart cities

    Freier Zugriff
    Tang, Jing / Wei, Xin / Zhao, Jialin et al. | IET | 2020
    Schlagwörter: semisupervised double duelling broad reinforcement learning , deep reinforcement learning approach , semisupervised learning , Q-learning network , supervised learning

    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: learning (artificial intelligence) , region-based deep convolutional neural network framework

    Research on deep learning method for rail surface defect detection

    Freier Zugriff
    Feng, Jiang Hua / Yuan, Hao / Hu, Yun Qing et al. | IET | 2020
    Schlagwörter: complex deep convolutional networks , learning (artificial intelligence) , deep learning method

    Real-time running detection system for UAV imagery based on optical flow and deep convolutional networks

    Freier Zugriff
    Wu, Qingtian / Zhou, Yimin / Wu, Xinyu et al. | IET | 2020
    Schlagwörter: deep convolutional networks , learning (artificial intelligence) , deep convolution networks , deep learning frameworks

    Real-time detection of distracted driving based on deep learning

    Freier Zugriff
    Tran, Duy / Manh Do, Ha / Sheng, Weihua et al. | IET | 2018
    Schlagwörter: learning (artificial intelligence) , deep convolutional neural networks , deep learning

    Rainfall-integrated traffic speed prediction using deep learning method

    Freier Zugriff
    Jia, Yuhan / Wu, Jianping / Ben-Akiva, Moshe et al. | IET | 2017
    Schlagwörter: learning (artificial intelligence) , deep testing , deep training , deep belief network , deep learning method

    Predicting driver behaviour at intersections based on driver gaze and traffic light recognition

    Freier Zugriff
    Rahman, Md. Junaedur / Beauchemin, Steven S. / Bauer, Michael A. | IET | 2021
    Schlagwörter: deep learning (artificial intelligence) , deep learning framework

    Pedestrian motion recognition via Conv-VLAD integrated spatial-temporal-relational network

    Freier Zugriff
    Peng, Shiyu / Su, Tingli / Jin, Xuebo et al. | IET | 2020
    Schlagwörter: learning (artificial intelligence) , deep information

    Multi-task deep learning with optical flow features for self-driving cars

    Freier Zugriff
    Hu, Yuan / Shum, Hubert P. H. / Ho, Edmond S. L. | IET | 2021
    Schlagwörter: multitask deep learning , learning (artificial intelligence) , supervised multitask deep network , self-supervised deep network

    Multi-receptive field graph convolutional neural networks for pedestrian detection

    Freier Zugriff
    Shen, Chao / Zhao, Xiangmo / Fan, Xing et al. | IET | 2019
    Schlagwörter: learning (artificial intelligence) , deep learning

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

    Freier Zugriff
    Zhang, Jinlei / Chen, Feng / Guo, Yinan et al. | IET | 2020
    Schlagwörter: deep-learning technologies