In modern war, the environment is complex and changeable, so how to detect and attack targets automatically and effectively is of great significance. In this paper, through the analysis of the characteristics of targets under complicated environment, six targets, the aeroplanes, bridges, vehicles, ships, submarines and tanks are selected as the objects to be detected, and a large number of corresponding images of them are collected via Internet, and with reference to the dataset format of PASCAL VOC [1], the collected six types of target images are manually annotated to set up the dataset. Then, a corresponding detection model which will be used to detect the six types of targets is built. Base on the dataset built earlier, the detection model is trained and improved by modify its anchors properly.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on Target Detection Based on Deep Learning


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Liao, Pengjun (author) / Xu, Jinxiang (author) / Guo, Shangkun (author) / Qu, Jingkun (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Target distance detection method based on deep learning

    ZHANG ZHONG / ZHANG XING / ZHANG JINFEI | European Patent Office | 2021

    Free access

    Research on the Development of Ship Target Detection Based on Deep Learning Technology

    Cui, Dongdong / Guo, Lijun / Zhang, Yongzhen | Springer Verlag | 2022


    Vehicle dense target detection method based on deep learning

    WU XIAO / ZHANG JI / XIANG CHONGYANG et al. | European Patent Office | 2021

    Free access

    UAV Aerial Photography Target Detection and Tracking Based on Deep Learning

    Li, Xiaohua / Wang, Feiyang / Xu, Aiming et al. | Springer Verlag | 2021


    UAV Aerial Photography Target Detection and Tracking Based on Deep Learning

    Li, Xiaohua / Wang, Feiyang / Xu, Aiming et al. | TIBKAT | 2022