As the main force of naval warfare, helicopters also require rapid identification and targeting of targets in addition to the detection of ship targets. From the current public information, it is known that helicopters mostly use optical targeting systems for target search, and pilots need to manually adjust the optical targeting video screen to confirm the targeting. In the complex background weather environment, the pilot confirms the target for a long time, which affects the combat efficiency. In recent years, the world pattern has changed, and various modern technologies have been applied to all aspects of the battlefield. Among them, automatic target recognition technology based on deep learning has become the most efficient application in the battlefield. In terms of business applications, Google, Facebook AI, and Tesla are all developing deep learning technologies. In this paper, the deep recognition model YOLO-V5 is used to train and learn the ship target set to meet the purpose of automatic aiming of helicopters for sea targets, and its accuracy and recall rate meet the requirements.


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    Title :

    Helicopter automatic aiming technology for sea targets based on deep learning


    Contributors:

    Conference:

    International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023) ; 2023 ; Changsha, China


    Published in:

    Proc. SPIE ; 12707


    Publication date :

    2023-06-08





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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