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The concept of sUAS/DL-based system for detecting and classifying abandoned small firearms

Defence Technology（防务技术） 2023年第12期30卷 23-31页

作者： Jungmok Ma Oleg A.Yakimenko Department of Defense Science Korea National Defense University(KNDU)Republic of Korea Department of systems Engineering Naval Postgraduate School(NPS)USA

Military object detection and identification is a key capability in surveillance and *** is a major factor in warfare effectiveness and warfighter ***,portable,and rapidly deployable small unmanned aerial systems(s UAS)in conjunction with powerful deep learning(DL)based object detection models are expected to play an important role for this *** prove overall feasibility of this approach,this paper discusses some aspects of designing and testing of an automated detection system to locate and identify small firearms left at the training range or at the *** a system is envisioned to involve an s UAS equipped with a modern electro-optical(EO)sensor and relying on a trained convolutional neural network(CNN).Previous study by the authors devoted to finding projectiles on the ground revealed certain challenges such as small object size,changes in aspect ratio and image scale,motion blur,occlusion,and *** study attempts to deal with these challenges in a realistic operational scenario and go further by not only detecting different types of firearms but also classifying them into different *** study used a YOLOv2CNN(Res Net-50 backbone network)to train the model with ground truth data and demonstrated a high mean average precision(m AP)of 0.97 to detect and identify not only small pistols but also partially occluded rifles.

关键词： small firearms Object detection Deep learning small unmanned aerial systems

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