计算机工程与应用 ›› 2024, Vol. 60 ›› Issue (8): 46-55.DOI: 10.3778/j.issn.1002-8331.2305-0372
谢威宇,张强
出版日期:
2024-04-15
发布日期:
2024-04-15
XIE Weiyu, ZHANG Qiang
Online:
2024-04-15
Published:
2024-04-15
摘要: 随着民用无人机产业的发展,无人机已经成为一项影响公共安全的重要问题。目前针对低空无人机的监视手段主要是采用雷达探测结合图像识别的方法,然而在图像检测识别中易受到与无人机同属“低、慢、小”目标的飞鸟的干扰。为了能够在基于可见光图像的无人机检测中排除飞鸟目标的干扰,利用深度神经网络对可见光图像中无人机与飞鸟进行精确的检测与分类,有效地排除飞鸟对无人机检测的干扰。系统阐释了目标检测技术的发展历程,讨论了各类基于深度学习网络目标检测算法的差异,对比了各类算法的优缺点。对可用于无人机与飞鸟检测的图像数据集进行了梳理与介绍,对相关研究的已有成果进行分析;再从实际应用出发,对无人机与飞鸟检测当中可能会存在的问题进行梳理,阐述与分析了能解决相应检测问题的卷积神经网络的相关研究。最后,针对该研究后续可能的发展方向进行展望。
谢威宇, 张强. 基于深度学习的图像中无人机与飞鸟检测研究综述[J]. 计算机工程与应用, 2024, 60(8): 46-55.
XIE Weiyu, ZHANG Qiang. Review on Detection of Drones and Birds in Photoelectric Images Based on Deep Learning Convolutional Neural Network[J]. Computer Engineering and Applications, 2024, 60(8): 46-55.
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