The present invention provides a road traffic flow detection method and system based on an unmanned aerial vehicle and a computer readable storage medium. The deep learning network of the SSD model is compressed and then vehicle detection is performed, so that lower power consumption and more lasting endurance are realized; a channel attention mechanism and a feature pyramid are introduced into the deep learning network of the SSD model, so that the detection result is more accurate, and detection coverage of all vehicle targets including small target vehicles is realized; and the method is applied to unmanned aerial vehicle detection, high detection precision is kept, and the endurance time of the unmanned aerial vehicle is prolonged.

    本发明提供了一种基于无人机的道路车流量检测方法、系统及计算机可读存储介质,对SSD模型的深度学习网络进行压缩后再进行车辆检测,实现了更低的功耗和更持久的续航;又通过对SSD模型的深度学习网络引入通道注意力机制、特征金字塔,使得检测结果更加精确,实现包括小目标车辆在内的所有车辆目标的检测覆盖;应用于无人机检测,既保留了检测高精度、又加大了无人机的续航时间。


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    Title :

    Road traffic flow detection method and system based on unmanned aerial vehicle, and computer readable storage medium


    Additional title:

    基于无人机的道路车流量检测方法、系统及计算机可读存储介质


    Contributors:
    LI CAIBO (author) / WANG XUN (author)

    Publication date :

    2021-06-04


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06K Erkennen von Daten , RECOGNITION OF DATA