To address safety issues caused by the increase availability and application of UAVs, automated detection systems are required. While such systems typically rely on a variety of sensor modalities, EO sensors are often a key modality. This is due to their comparatively low cost and direct intepretability by human operators. Besides automated detection of UAVs in EO imagery, classification of a UAV’s type is an important task to assess the degree of potential safety risk. While the applicability of deep learning based UAV detection in EO imagery has already been demonstrated, this work is the first to examine the potential of deep learning based UAV type classification in EO imagery. We evaluate multiple deep learning based detectors trained to classify UAV types as well as a cascade of an initial detector followed by a separate classifier. Our evaluation is carried out on publicly available data, supplemented by a few self-recorded sequences, and focuses on aspects like class balancing, UAV size, image scale and classification backbone architectures. We further analyse a class confusion matrix to better understand occurring classification errors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Deep learning based UAV type classification


    Contributors:

    Conference:

    Pattern Recognition and Tracking XXXII ; 2021 ; Online Only,Florida,United States


    Published in:

    Proc. SPIE ; 11735


    Publication date :

    2021-04-12





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Deep Learning-Based Vehicle Classification

    Muhib, Raghib Barkat / Ahmad, Imran Shafiq / Boufama, Boubakeur | Springer Verlag | 2023


    Vehicle Counting System Based on Vehicle Type Classification Using Deep Learning Method

    Awang, Suryanti / Azmi, Nik Mohamad Aizuddin Nik | Springer Verlag | 2017


    Deep Learning Based Approach for Gender Classification

    Haseena, S. / Bharathi, S. / Padmapriya, I. et al. | IEEE | 2018


    Deep Learning for Radar Classification

    Holt, Danny / Guo, Weisi / Sun, Mengwei et al. | IEEE | 2024


    Weather Classification for Lidar based on Deep Learning

    Ma, Bing / Wang, Dengjiang / Ma, Gang et al. | SAE Technical Papers | 2022