1–20 von 123 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. | Wiley | 2020
    Schlagwörter: structured convolutional neural networks model , overfitting‐preventing deep neural network , convolutional 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. | IET | 2020
      Schlagwörter: convolutional neural nets , structured convolutional neural networks model , overfitting-preventing deep neural network

    Vehicle detection systems for intelligent driving using deep convolutional neural networks

    Freier Zugriff
    Rahib Abiyev / Murat Arslan | DOAJ | 2023
    Schlagwörter: Deep learning , Convolutional neural network

    Vehicle Color Recognition With Spatial Pyramid Deep Learning

    Hu, Chuanping | Online Contents | 2015
    Schlagwörter: deep learning , convolutional neural network (CNN) , Neural networks

    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

    Ultra-Wideband Localization and Deep-Learning-Based Plant Monitoring Using Micro Air Vehicles

    Ching, Poh Ling / Tan, Shu Chuan / Ho, Hann Woei | AIAA | 2022
    Schlagwörter: Deep Convolutional Neural Network

    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)

    Trajectory-level fog detection based on in-vehicle video camera with TensorFlow deep learning utilizing SHRP2 naturalistic driving data

    Khan, Md Nasim / Ahmed, Mohamed M. | Elsevier | 2020
    Schlagwörter: Deep Learning , Deep Neural Network , Recurrent Neural Network , 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

    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

    Terrain classification using mars raw images based on deep learning algorithms with application to wheeled planetary rovers

    Guo, Junlong / Zhang, Xingyang / Dong, Yunpeng et al. | Elsevier | 2023
    Schlagwörter: Deep convolutional neural network

    Supervised learning mixing characteristics of film cooling in a rocket combustor using convolutional neural networks

    Ma, Hao / Zhang, Yu-xuan / Haidn, Oskar J. et al. | Elsevier | 2020
    Schlagwörter: Deep learning , 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

      Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

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

    Spatiotemporal Image-Based Flight Trajectory Clustering Model with Deep Convolutional Autoencoder Network

    Liu, Ye / Ng, Kam K. H. / Chu, Nana et al. | AIAA | 2023
    Schlagwörter: Deep Convolutional Neural Network , Deep Learning

    Space Objects Classification via Light-Curve Measurements Using Deep Convolutional Neural Networks

    Linares, Richard / Furfaro, Roberto / Reddy, Vishnu | Springer Verlag | 2020
    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

    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

    Sistem Pengenal Isyarat Tangan Untuk Mengendalikan Gerakan Robot Beroda menggunakan Convolutional Neural Network

    Freier Zugriff
    Adi, Habib Astari / Candradewi, Ika | BASE | 2019
    Schlagwörter: deep learning , convolutional neural network

    Simulated Evaluation of Navigation System for Multi-quadrotor Coordination in Search and Rescue

    Rafikh, Rayyan Muhammad / D’Souza, Jeane Marina | Springer Verlag | 2023
    Schlagwörter: Convolutional neural network , Deep learning

    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

    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