This paper focuses on the application of image classification in forest fire detection using unmanned aerial vehicles (UAVs), discussing the development history of UAV image classification and the significance of machine vision in fire monitoring. Initially, the dataset used for fire detection and the data processing and enhancement techniques are introduced. Subsequently, the construction and architecture of the image classification model are detailed. The core of this study is to enhance the accuracy of model image recognition in complex forest environments by replacing optimizers, modifying the model architecture, and adding modules. Various models and optimizers are compared and analyzed, and the operations and significance of enhancement methods and attention mechanisms are explored. The aim is to improve training effectiveness through these strategies, thereby effectively supporting UAVs in forest fire detection.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Application of image classification in forest fire detection using UAV


    Beteiligte:
    Geng, Bowen (Autor:in)


    Erscheinungsdatum :

    05.07.2024


    Format / Umfang :

    629659 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    UAV-based forest fire detection and tracking using image processing techniques

    Yuan, Chi / Liu, Zhixiang / Zhang, Youmin | IEEE | 2015


    Fire detection using infrared images for UAV-based forest fire surveillance

    Yuan, Chi / Liu, Zhixiang / Zhang, Youmin | IEEE | 2017



    CoFFI: An Image Classification GUI for Forest Fire Imagery Applying Convolution Neural Networks

    Azami, Muhammad Hasif Bin / Orger, Necmi Cihan / Schulz, Victor et al. | TIBKAT | 2023