Soil organic matter prediction model with satellite hyperspectral image based on optimized denoising method
X Meng, Y Bao, Q Ye, H Liu, X Zhang, H Tang… - Remote Sensing, 2021 - mdpi.com
In order to improve the signal-to-noise ratio of the hyperspectral sensors and exploit the
potential of satellite hyperspectral data for predicting soil properties, we took MingShui …
potential of satellite hyperspectral data for predicting soil properties, we took MingShui …
Automated detection of diabetes from exhaled human breath using deep hybrid architecture
In this paper, we have proposed an automated medical system for detecting type 2 diabetes
from exhaled breath. Human breath can be used as a diagnostic sample for detecting many …
from exhaled breath. Human breath can be used as a diagnostic sample for detecting many …
Low-SNR recognition of UAV-to-ground targets based on micro-Doppler signatures using deep convolutional denoising encoders and deep residual learning
The rapid development of flight control technology has made unmanned aerial vehicles
(UAVs) widely used in high-precision strikes on the battlefield. The premise of this is to …
(UAVs) widely used in high-precision strikes on the battlefield. The premise of this is to …
Classification of UAV-to-ground targets based on micro-Doppler fractal features using IEEMD and GA-BP neural network
In modern wars, the unmanned aerial vehicles (UAVs) have become the main means of
local high-precision strike. The ground tracked vehicle and the ground wheeled vehicle are …
local high-precision strike. The ground tracked vehicle and the ground wheeled vehicle are …
A reawakening of machine learning application in unmanned aerial vehicle: future research motivation
Abstract Machine learning (ML) entails artificial procedures that improve robotically through
experience and using data. Supervised, unsupervised, semi-supervised, and Reinforcement …
experience and using data. Supervised, unsupervised, semi-supervised, and Reinforcement …
Classification of UAV-to-ground vehicles based on micro-Doppler effect and bispectrum analysis
Vehicles such as armored cars and tanks have a big threat due to their flexibility and lethality
in modern wars. In order to destroy them without casualties, the unmanned aerial vehicles …
in modern wars. In order to destroy them without casualties, the unmanned aerial vehicles …
Micro-Doppler-Coded Drone Identification
The forthcoming era of massive drone delivery deployment in urban environments raises a
need to develop reliable control and monitoring systems. While active solutions, ie, wireless …
need to develop reliable control and monitoring systems. While active solutions, ie, wireless …
Polarimetric detection of endo-clutter UAV in a low-grazing geometry
M Rozel - 2023 - theses.hal.science
In the past decades, Unmanned Aerial Vehicles have benefited from the miniaturization of
electronic components, allowing for cheap and small drone designs, and allowing a rapid …
electronic components, allowing for cheap and small drone designs, and allowing a rapid …
Micro Doppler reconstruction from discontinuous observations based on gapped SBL-FBTVAR method for spin stabilized object
L Hong, F Dai, X Wang - IEEE Access, 2019 - ieeexplore.ieee.org
Micro Doppler analysis of spin stabilized objects is of a great significance for attitude
estimation and recognition of space targets. In practice, the radar cannot dwell on one target …
estimation and recognition of space targets. In practice, the radar cannot dwell on one target …
[PDF][PDF] A Matching Pursuit-Based Vehicle Wheel Parameter Extraction Method from Micro-Doppler Radar Signal.
L Zhang, C Yifan, LIU Shuo, ZOU Bin - Radioengineering, 2021 - radioeng.cz
Micro-Doppler effects of moving vehicles in a radar system are mainly induced by the
rotation of wheels, whose features are closely related to the numbers, positions and …
rotation of wheels, whose features are closely related to the numbers, positions and …