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    Physical, data-driven and hybrid approaches to model engine exhaust gas temperatures in operational conditions

    Freier Zugriff
    Coraddu, Andrea / Oneto, Luca / Cipollini, Francesca et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: multitask learning

    Multidomain Joint Learning of Pedestrian Detection for Application to Quadrotors

    Freier Zugriff
    Yuan-Kai Wang / Jonathan Guo / Tung-Ming Pan | DOAJ | 2022
    Schlagwörter: multitask learning , multidomain joint learning

    Ant colony optimisation for coloured travelling salesman problem by multi-task learning

    Freier Zugriff
    Dong, Xueshi / Dong, Wenyong / Cai, Yongle | IET | 2018
    Schlagwörter: learning (artificial intelligence) , cooperative learning , multitask cooperative learning approach

    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

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

    Freier Zugriff
    Hu, Yuan / Shum, Hubert P. H. / Ho, Edmond S. L. | Wiley | 2020
    Schlagwörter: multitask deep learning , supervised multitask deep network , learning (artificial intelligence)

    Deep Multitask Learning for Railway Track Inspection

    Gibert, Xavier | Online Contents | 2017
    Schlagwörter: multitask learning

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

    Freier Zugriff
    Yan, Zhuo / Feng, Youji / Cheng, Cheng et al. | IET | 2017
    Schlagwörter: multitask learning , learning (artificial intelligence)

    Ant colony optimisation for coloured travelling salesman problem by multi‐task learning

    Freier Zugriff
    Dong, Xueshi / Dong, Wenyong / Cai, Yongle | Wiley | 2018
    Schlagwörter: multitask cooperative learning approach , learning (artificial intelligence) , cooperative learning

    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: multitask learning , learning (artificial intelligence)

    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: transfer learning , multitask learning , learning (artificial intelligence) , structured learning approach

    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

    Vehicle Type Classification Using a Semisupervised Convolutional Neural Network

    Zhen Dong | Online Contents | 2015
    Schlagwörter: feature learning , sparse Laplacian filter learning , handcrafted visual feature learning , multitask learning , learning (artificial intelligence) , filter 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) , scale-aware multitask region proposal network module

    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 cascaded multitask framework , learning (artificial intelligence)

    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: learning (artificial intelligence) , deep cascaded multitask framework

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