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keywords:( deep learning)

    GPS-based citywide traffic congestion forecasting using CNN-RNN and C3D hybrid model

    Guo, Jingqiu / Liu, Yangzexi / Yang, Qingyan (Ken) et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Deep Q learning-based traffic signal control algorithms: Model development and evaluation with field data

    Wang, Hao / Yuan, Yun / Yang, Xianfeng Terry et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep neural network , deep reinforcement learning , Q-learning

    Deep Reinforcement Learning for Drone Delivery

    Freier Zugriff
    Guillem Muñoz / Cristina Barrado / Ender Çetin et al. | DOAJ | 2019
    Schlagwörter: deep learning , reinforcement learning , Q-learning

    A data-driven lane-changing behavior detection system based on sequence learning

    Gao, Jun / Murphey, Yi Lu / Yi, Jiangang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: sequence learning , deep LSTM

    Online longitudinal trajectory planning for connected and autonomous vehicles in mixed traffic flow with deep reinforcement learning approach

    Cheng, Yanqiu / Hu, Xianbiao / Chen, Kuanmin et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep Q-learning , reinforcement learning

    Convolutional neural network for detecting railway fastener defects using a developed 3D laser system

    Zhan, You / Dai, Xianxing / Yang, Enhui et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    A Survey of Offline- and Online-Learning-Based Algorithms for Multirotor Uavs

    Freier Zugriff
    Serhat Sönmez / Matthew J. Rutherford / Kimon P. Valavanis | DOAJ | 2024
    Schlagwörter: offline learning , online learning , reinforcement learning , deep learning , machine learning

    Multi-UAV Cooperative Offensive Combat Intelligent Planning Based on Deep Reinforcement Learning

    Freier Zugriff
    LI Junsheng / YUE Longfei / ZUO Jialiang et al. | DOAJ | 2022
    Schlagwörter: deep learning , deep reinforcement learning

    A cold-start-free reinforcement learning approach for traffic signal control

    Xiao, Nan / Yu, Liang / Yu, Jinqiang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning , reinforcement learning

    Real-time traffic incident detection based on a hybrid deep learning model

    Li, Linchao / Lin, Yi / Du, Bowen et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Deep machine learning for structural health monitoring on ship hulls using acoustic emission method

    Karvelis, Petros / Georgoulas, George / Kappatos, Vassilios et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning , deep belief networks

    Graph attention temporal convolutional network for traffic speed forecasting on road networks

    Zhang, Ke / He, Fang / Zhang, Zhengchao et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Road Pothole Detection Using Unmanned Aerial Vehicle Imagery and Deep Learning Technique

    Freier Zugriff
    Dana Mohammed Ali / Haval A.Sadeq | DOAJ | 2022
    Schlagwörter: deep learning

    Drones Chasing Drones: Reinforcement Learning and Deep Search Area Proposal

    Freier Zugriff
    Moulay A. Akhloufi / Sebastien Arola / Alexandre Bonnet | DOAJ | 2019
    Schlagwörter: deep learning , reinforcement learning

    Energy-Efficient Inference on the Edge Exploiting TinyML Capabilities for UAVs

    Freier Zugriff
    Wamiq Raza / Anas Osman / Francesco Ferrini et al. | DOAJ | 2021
    Schlagwörter: machine learning , deep learning

    SUST-DDD: A Real-Drive Dataset for Driver Drowsiness Detection

    Freier Zugriff
    Esra Kavalci Yilmaz / M. Ali Akcayol | DOAJ | 2022
    Schlagwörter: deep learning

    Automatic Road Pavement Distress Recognition Using Deep Learning Networks from Unmanned Aerial Imagery

    Freier Zugriff
    Farhad Samadzadegan / Farzaneh Dadrass Javan / Farnaz Ashtari Mahini et al. | DOAJ | 2024
    Schlagwörter: deep learning network , YOLOv8 Deep Learning Network

    DRL-based adaptive signal control for bus priority service under connected vehicle environment

    Zhang, Xinshao / He, Zhaocheng / Zhu, Yiting et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep reinforcement learning

    Multiple-UAV Reinforcement Learning Algorithm Based on Improved PPO in Ray Framework

    Freier Zugriff
    Guang Zhan / Xinmiao Zhang / Zhongchao Li et al. | DOAJ | 2022
    Schlagwörter: deep reinforcement learning , curriculum learning

    Decentralized Learning and Model Averaging Based Automatic Modulation Classification in Drone Communication Systems

    Freier Zugriff
    Min Ma / Yunhe Xu / Zhi Wang et al. | DOAJ | 2023
    Schlagwörter: deep learning , deep neural network , decentralized learning

    Vision-Based Deep Reinforcement Learning of UAV-UGV Collaborative Landing Policy Using Automatic Curriculum

    Freier Zugriff
    Chang Wang / Jiaqing Wang / Changyun Wei et al. | DOAJ | 2023
    Schlagwörter: deep reinforcement learning , automatic curriculum learning

    Development of a global road safety performance function using deep neural networks

    Freier Zugriff
    Guangyuan Pan / Liping Fu / Lalita Thakali | DOAJ | 2017
    Schlagwörter: Deep learning

    Machine Learning for Precision Agriculture Using Imagery from Unmanned Aerial Vehicles (UAVs): A Survey

    Freier Zugriff
    Imran Zualkernan / Diaa Addeen Abuhani / Maya Haj Hussain et al. | DOAJ | 2023
    Schlagwörter: machine learning , deep learning

    DLW-Net model for traffic flow prediction under adverse weather

    Yao, Ronghan / Zhang, Wensong / Long, Meng | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft

    Freier Zugriff
    Uğur Kılıç | DOAJ | 2023
    Schlagwörter: machine learning , deep learning

    Deep Reinforcement Learning with Corrective Feedback for Autonomous UAV Landing on a Mobile Platform

    Freier Zugriff
    Lizhen Wu / Chang Wang / Pengpeng Zhang et al. | DOAJ | 2022
    Schlagwörter: deep reinforcement learning , interactive learning

    Deep Learning Classification of 2D Orthomosaic Images and 3D Point Clouds for Post-Event Structural Damage Assessment

    Freier Zugriff
    Yijun Liao / Mohammad Ebrahim Mohammadi / Richard L. Wood | DOAJ | 2020
    Schlagwörter: deep learning , transfer learning

    Development of a novel engine power model to estimate heavy-duty truck fuel consumption

    Kan, Yuheng / Liu, Hao / Lu, Xiaoyun et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Towards Fully Autonomous Drone Tracking by a Reinforcement Learning Agent Controlling a Pan–Tilt–Zoom Camera

    Freier Zugriff
    Mariusz Wisniewski / Zeeshan A. Rana / Ivan Petrunin et al. | DOAJ | 2024
    Schlagwörter: reinforcement learning , deep learning , machine learning

    Forecasting citywide short-term turning traffic flow at intersections using an attention-based spatiotemporal deep learning model

    Jia, Tao / Cai, Chenxi | Taylor & Francis Verlag | 2023
    Schlagwörter: Deep learning

    Electric vehicle charging demand forecasting using deep learning model

    Yi, Zhiyan / Liu, Xiaoyue Cathy / Wei, Ran et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Deep Architecture for Citywide Travel Time Estimation Incorporating Contextual Information

    Tang, Kun / Chen, Shuyan / Khattak, Aemal J. et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Connected autonomous vehicles for improving mixed traffic efficiency in unsignalized intersections with deep reinforcement learning

    Freier Zugriff
    Bile Peng / Musa Furkan Keskin / Balázs Kulcsár et al. | DOAJ | 2021
    Schlagwörter: Deep reinforcement learning

    Development of LSTM-MLR hybrid model for radar detector missing and outlier traffic volume correction

    Kim, Dohoon / Kim, Eungcheol | Taylor & Francis Verlag | 2023
    Schlagwörter: deep-learning

    Autonomous Unmanned Aerial Vehicles in Bushfire Management: Challenges and Opportunities

    Freier Zugriff
    Shouthiri Partheepan / Farzad Sanati / Jahan Hassan | DOAJ | 2023
    Schlagwörter: machine learning , deep learning

    A Study of Correlation between Fishing Activity and AIS Data by Deep Learning

    Freier Zugriff
    Kuan Yu Shen / Ying Jui Chu / Shwu Jing Chang et al. | DOAJ | 2020
    Schlagwörter: deep learning framework , deep learning , learning methods

    Characterizing parking systems from sensor data through a data-driven approach

    Arjona Martinez, Jamie / Linares, Maria Paz / Casanovas, Josep | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Task Allocation of Multiple Unmanned Aerial Vehicles Based on Deep Transfer Reinforcement Learning

    Freier Zugriff
    Yongfeng Yin / Yang Guo / Qingran Su et al. | DOAJ | 2022
    Schlagwörter: deep reinforcement learning , transfer learning

    Video-based trajectory extraction with deep learning for High-Granularity Highway Simulation (HIGH-SIM)

    Freier Zugriff
    Xiaowei Shi / Dongfang Zhao / Handong Yao et al. | DOAJ | 2021
    Schlagwörter: Deep learning

    Deep neural network based data-driven virtual sensor in vehicle semi-active suspension real-time control

    Freier Zugriff
    Paulius Kojis / Eldar Šabanovič / Viktor Skrickij | DOAJ | 2022
    Schlagwörter: deep neural network , deep learning

    Datensatz von Grundrissen eines generischen Bahnhofsmodells und zugehörige neuronale Netze zur Vorhersage von Personenstromsimulation-Daten

    Freier Zugriff
    TU München | Mobilithek
    Schlagwörter: Deep Learning

    The Study on a Fighter Against a Medium-range Air-to-air Missile Based on Deep Deterministic Policy Gradient Algorithm

    Freier Zugriff
    SONG Hongchuan / ZHAN Hao / XIA Lu et al. | DOAJ | 2021
    Schlagwörter: deep deterministic policy gradient , deep reinforcement learning

    Uplink Throughput Maximization in UAV-Aided Mobile Networks: A DQN-Based Trajectory Planning Method

    Freier Zugriff
    Yuping Lu / Ge Xiong / Xiang Zhang et al. | DOAJ | 2022
    Schlagwörter: deep reinforcement learning , Q-learning

    Deep Neural Networks and Transfer Learning for Food Crop Identification in UAV Images

    Freier Zugriff
    Robert Chew / Jay Rineer / Robert Beach et al. | DOAJ | 2020
    Schlagwörter: machine learning , deep learning

    Vehicle detection and masking in UAV images using YOLO to improve photogrammetric products

    Freier Zugriff
    Pargieła Karolina | DOAJ | 2022
    Schlagwörter: deep learning

    Automated Agave Detection and Counting Using a Convolutional Neural Network and Unmanned Aerial Systems

    Freier Zugriff
    Donovan Flores / Iván González-Hernández / Rogelio Lozano et al. | DOAJ | 2021
    Schlagwörter: deep learning

    Development of a Signal-Free Intersection Control System for CAVs and Corridor Level Impact Assessment

    Freier Zugriff
    Ardeshir Mirbakhsh / Joyoung Lee / Dejan Besenski | DOAJ | 2023
    Schlagwörter: deep reinforcement learning , deep queue networks , machine learning

    Deep Learning and Artificial Neural Networks for Spacecraft Dynamics, Navigation and Control

    Freier Zugriff
    Stefano Silvestrini / Michèle Lavagna | DOAJ | 2022
    Schlagwörter: deep learning

    Multiple Unmanned Aerial Vehicle Autonomous Path Planning Algorithm Based on Whale-Inspired Deep Q-Network

    Freier Zugriff
    Wenshan Wang / Guoyin Zhang / Qingan Da et al. | DOAJ | 2023
    Schlagwörter: deep reinforcement learning , deep Q-network

    Review of intelligent detection and statistical methods of wild animals in UAV aerial photography

    Freier Zugriff
    ZHU Ninghua / ZHENG Jiangbin / ZHANG Yang | DOAJ | 2023
    Schlagwörter: deep learning , transfer learning

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