[引用][C] Convolutional Neural Network-Based UAV Classification Using RF Fingerprints
Unmanned aerial vehicle (UAV) detection issues can be successfully resolved by machine
learning (ML) algorithms effectively. This research presents a developing ML approach …
learning (ML) algorithms effectively. This research presents a developing ML approach …
Micro-UAV detection and classification from RF fingerprints using machine learning techniques
This paper focuses on the detection and classification of micro-unmanned aerial vehicles
(UAVs) using radio frequency (RF) fingerprints of the signals transmitted from the controller …
(UAVs) using radio frequency (RF) fingerprints of the signals transmitted from the controller …
RF-based drone classification under complex electromagnetic environments using deep learning
H Zhang, T Li, Y Li, J Li, OA Dobre… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Recent studies have demonstrated that using deep-learning (DL) methods to classify drones
based on the radio-frequency (RF) signal is effective. As known, the rich and diverse data is …
based on the radio-frequency (RF) signal is effective. As known, the rich and diverse data is …
Classification of UAVs utilizing fixed boundary empirical wavelet sub-bands of RF fingerprints and deep convolutional neural network
K Bremnes, R Moen, SR Yeduri… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) classification and identification have many applications in a
variety of fields, including UAV tracking systems, antidrone systems, intrusion detection …
variety of fields, including UAV tracking systems, antidrone systems, intrusion detection …
RF Signal Classification-based Drone Identification with Multimodal Database
The aim of this paper is to conduct a comprehensive review of existing UAV classification
and identification methods. We will analyze the evolution of these methods and propose an …
and identification methods. We will analyze the evolution of these methods and propose an …
[HTML][HTML] Rf-enabled deep-learning-assisted drone detection and identification: An end-to-end approach
The security and privacy risks posed by unmanned aerial vehicles (UAVs) have become a
significant cause of concern in today's society. Due to technological advancement, these …
significant cause of concern in today's society. Due to technological advancement, these …
Radio frequency fingerprint-based drone identification and classification using Mel spectrograms and pre-trained YAMNet neural
The convergence of drones with the Internet of Things (IoT) has paved the way for the
Internet of Drones (IoD), an interconnected network of drones, ground control systems, and …
Internet of Drones (IoD), an interconnected network of drones, ground control systems, and …
Signal fingerprinting and machine learning framework for UAV detection and identification.
OO Medaiyese - 2021 - ir.library.louisville.edu
Advancement in technology has led to creative and innovative inventions. One such
invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now …
invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now …
RF Signal-Based Multipurpose UAV Surveillance System Using Deep Neural Network
Drones, also known as Unmanned Aerial Vehicles (UAV), have recently become
increasingly popular due to substantial cost reductions and technological advancements …
increasingly popular due to substantial cost reductions and technological advancements …
Adaptive RF fingerprint decomposition in micro UAV detection based on machine learning
Radio frequency (RF) signal classification has significantly been used for detecting and
identifying the features of unknown unmanned aerial vehicles (UAVs). This paper proposes …
identifying the features of unknown unmanned aerial vehicles (UAVs). This paper proposes …