Anomaly-Based Drone Classification Using a Model Trained Convolutional Neural Network Autoencoder on Radar Micro-Doppler
Author:
Affiliation:
1. KTH Royal Institute of Technology,Division of Information Science and Engineering,Stockholm,Sweden
2. SAAB AB,Product Unit Electronic Surveillance Business Area Surveillance,Stockholm,Sweden
Funder
European Research Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10371000/10371001/10371163.pdf?arnumber=10371163
Reference23 articles.
1. Machine Learning-Based Drone Detection and Classification: State-of-the-Art in Research
2. Target Detection and Classification of Small Drones by Deep Learning on Radar Micro-Doppler
3. Classification of drones and birds using convolutional neural networks applied to radar micro‐Doppler spectrogram images
4. Detecting drones with radars and convolutional networks based on micro-Doppler signatures
5. Convolutional Neural Networks for Robust Classification of Drones
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