DroneSense: The Identification, Segmentation, and Orientation Detection of Drones via Neural Networks
Author:
Affiliation:
1. School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K.
2. School of Engineering, The University of Edinburgh, Edinburgh, U.K.
Funder
Defence Science Technologies Laboratory
Engineering and Physical Sciences Research Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09743918.pdf?arnumber=9743918
Reference122 articles.
1. Analysis of commercial drone sounds and its identification
2. Distinguishing Drone Types Based on Acoustic Wave by IoT Device
3. Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
4. Empirical study of drone sound detection in real-life environment with deep neural networks
5. Improving Smart Cities Safety Using Sound Events Detection Based on Deep Neural Network Algorithms
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