1–20 von 388 Ergebnissen
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    Виявлення літаків на зображеннях з повітря з використанням нейронної мережі YOLO

    Freier Zugriff
    Volodymyr Kharchenko / Iurii Chyrka | DOAJ | 2018
    Schlagwörter: convolutional neural network

    YOLOv4 Object Detection Model for Nondestructive Radiographic Testing in Aviation Maintenance Tasks

    Chen, Zhi-Hao / Juang, Jyh-Ching | AIAA | 2021
    Schlagwörter: Convolutional Neural Network

    Wire Databases Generation Using Deep Learning Methods for Rotorcraft Wire Strike Prevention

    Achour, Gabriel / Harris, Caleb / Payan, Alexia P. et al. | AIAA | 2024
    Schlagwörter: Convolutional Neural Network , Pole Locations and Wire Network Prediction

    Weather and surface condition detection based on road-side webcams: Application of pre-trained Convolutional Neural Network

    Freier Zugriff
    Md Nasim Khan / Mohamed M. Ahmed | DOAJ | 2022
    Schlagwörter: Convolutional Neural Network

    Wave Detection and Tracking Within a Rotating Detonation Engine Through Object Detection

    Johnson, Kristyn B. / Ferguson, Donald H. / Nix, Andrew C. et al. | AIAA | 2023
    Schlagwörter: Convolutional Neural Network

    Visual Subterranean Junction Recognition for MAVs based on Convolutional Neural Networks

    Freier Zugriff
    Mansouri, Sina Sharif / Karvelis, Petros / Kanellakis, Christoforos et al. | BASE | 2019
    Schlagwörter: Convolutional Neural Network

    Visual odometry with depth-wise separable convolution and quaternion neural networks

    Freier Zugriff
    De Magistris G. / Comminiello D. / Napoli C. et al. | BASE | 2023
    Schlagwörter: convolutional neural network , recurrent neural network , neural-network

    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

    Vision-Based Pose Estimation of Fixed-Wing Aircraft Using You Only Look Once and Perspective-n-Points

    Kim, Sukkeun / Kim, Jeongho / Park, Jihoon et al. | AIAA | 2021
    Schlagwörter: Convolutional Neural Network

    Velocity Measurement Improvement of Landing Radar Considering Irradiated Surface Using Neural Networks

    Hidaka, Moeko / Takahashi, Masaki / Ishida, Takayuki et al. | AIAA | 2020
    Schlagwörter: Convolutional Neural Network

    Vehicle Type Classification Using a Semisupervised Convolutional Neural Network

    Zhen Dong | Online Contents | 2015
    Schlagwörter: neural nets , Neural networks , semisupervised convolutional neural network , neural network

    Vehicle detection systems for intelligent driving using deep convolutional neural networks

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

    Vehicle Color Recognition With Spatial Pyramid Deep Learning

    Hu, Chuanping | Online Contents | 2015
    Schlagwörter: 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 , recurrent 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
    Md. Hishamur Rahman / Shakil Mohammad Rifaat | DOAJ | 2021
    Schlagwörter: Neural nets , convolutional neural network

    Using Deep Neural Networks to Separate Entangled Workpieces in Random Bin Picking

    Moosmann, Marius / Spenrath, Felix / Mönnig, Manuel et al. | Springer Verlag | 2021
    Schlagwörter: Convolutional neural network

    Using CNN-LSTM to predict signal phasing and timing aided by High-Resolution detector data

    Islam, Zubayer / Abdel-Aty, Mohamed / Mahmoud, Nada | Elsevier | 2022
    Schlagwörter: Convolutional Neural Network , Network

    Use of Thermal Imagery for Robust Moving Object Detection

    Freier Zugriff
    Bergenroth, Hannah | BASE | 2021
    Schlagwörter: convolutional neural network

    Urban traffic flow online prediction based on multi‐component attention mechanism

    Freier Zugriff
    Sun, Bo / Sun, Tuo / Zhang, Yujia et al. | Wiley | 2020
    Schlagwörter: recurrent neural nets , recurrent neural network , one‐dimensional convolutional neural network , convolutional neural nets

      Urban traffic flow online prediction based on multi-component attention mechanism

      Freier Zugriff
      Sun, Bo / Sun, Tuo / Zhang, Yujia et al. | IET | 2020
      Schlagwörter: convolutional neural nets , one-dimensional convolutional neural network , recurrent neural network , recurrent neural nets

    Universiti Malaysia Pahang Autonomous Shuttle Development: Lane Classification Analysis Using Convolutional Neural Network (CNN)

    Yee, Lee Yin / Zakaria, Muhammad Aizzat | Springer Verlag | 2022
    Schlagwörter: Convolutional Neural Network