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An Initial Investigation into Using Convolutional Neural Networks for Classification of Drones

机译：使用卷积神经网络进行无人机分类的初步研究

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The use of convolutional neural networks (CNNs) in drone and non-drone classification is investigated in this paper. A classifier is trained on radar spectrograms obtained using an L-band staring radar and the performance is assessed and compared with a machine learning benchmark. Initial results have shown the CNN to achieve a correct classification performance of up to 98.89%.

机译：本文研究了卷积神经网络（CNN）在无人机和非无人机分类中的应用。使用L波段凝视雷达对分类器进行雷达频谱图训练，并评估性能并将其与机器学习基准进行比较。初步结果显示，CNN可以实现高达98.89％的正确分类性能。

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《International Radar Conference》|2020年|618-623|共6页
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Holly Dale; Chris Baker; Michail Antoniou; Mohammed Jahangir;
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关键词
classification; deep learning; signal processing; machine learning; staring radar; UAVs; birds;

机译：分类;深度学习;信号处理;机器学习;凝视雷达;无人机;鸟类;

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专利

1. Classification of drones and birds using convolutional neural networks applied to radar micro-Doppler spectrogram images [J] . Rahman Samiur, Robertson Duncan A. Radar, Sonar & Navigation, IET . 2020,第5期

机译：使用卷积神经网络应用于雷达微多普勒谱图图像的无人机和鸟类的分类
2. Drone Classification Using Convolutional Neural Networks With Merged Doppler Images [J] . Byung Kwan Kim, Hyun-Seong Kang, Seong-Ook Park IEEE Geoscience and Remote Sensing Letters . 2017,第1期

机译：使用卷积神经网络合并多普勒图像的无人机分类
3. Application of Deep Convolutional Neural Networks in Attention-Deficit/Hyperactivity Disorder Classification: Data Augmentation and Convolutional Neural Network Transfer Learning [J] . Zhu Li, Chang Weike Journal of Medical Imaging and Health Informatics . 2019,第8期

机译：深度卷积神经网络在注意力缺陷/多动障碍分类中的应用：数据增强与卷积神经网络转移学习
4. A Comparison of Convolutional Neural Networks for Low SNR Radar Classification of Drones [C] . Holly Dale, Chris Baker, Michail Antoniou, IEEE Radar Conference . 2021

机译：卷积神经网络对无人机低SNR雷达分类的比较
5. Investigating Noise Robustness of Convolutional Neural Networks for Image Classification Using Gabor Filters [D] . Jeong, Sangwon. 2020

机译：使用Gabor过滤器调查卷积神经网络的噪声稳健性
6. 3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts [O] . Ibon Merino, Jon Azpiazu, Anthony Remazeilles, 2021

机译：3D卷积神经网络从佩带的2D卷积神经网络初始化用于工业部件的分类
7. Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks [O] . Somayeh Nezami, Ehsan Khoramshahi, Olli Nevalainen, 2020

机译：深度学习卷积神经网络的无人驾驶高光谱和RGB图像的树种分类

An Initial Investigation into Using Convolutional Neural Networks for Classification of Drones

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