基于深度学习的智能化无人机视觉系统设计OACSTPCD
Design of intelligent UAV vision system based on deep learning technology
针对无人机飞行高度高、目标尺度变化大、目标存在密集遮挡等问题,本文将对基于深度学习的无人机目标探测与识别以及视觉定位进行深入探讨,并设计出一套无人机目标探测与定位系统.研究选用Yolov5深度学习网络模型进行目标检测,基于Darknet深度学习框架完成端到端的训练预测,最后利用AprilTag视觉基准库完成无人机自身空间位置的辅助定位.测试结果表明,Yolov5模型的参数量只有5.3,准确率为97.41％,召回率为90.73％,mAP为83.2.…查看全部>>
To address the problems challenges such as high flight altitude,large changes in target scale,and the densely occluded tar-gets,the study utilizes deep learning methods for target detection and identification and visual localization of UAV.A UAV target detec-tion and positioning system is designed and discussed in depth.The study selects Yolov5 deep learning network model for target detec-tion,completes end-to-end training prediction based on Darknet deep le…查看全部>>
陈忠财;李鑫;隋立林
国能新疆托克逊能源有限责任公司,托克逊 838100国能新疆托克逊能源有限责任公司,托克逊 838100国能数智科技开发(北京)有限公司,北京 100011
电子信息工程
无人机深度学习目标检测视觉定位Yolov5
unmanned aircraftdeep learningtarget detectionvisual localizationYolov5
《集成电路与嵌入式系统》 2024 (9)
62-67,6
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