Positioning Errors of Objects Measured by Convolution Neural Network in Unmanned Aerial Vehicle Images

The conversion of unmanned aerial vehicles (UAVs, also called drones) and convolution neural network (CNN) facilitates the location of objects in real time using their sensors. In photogrammetry, the positional accuracy of objects is directly affected by the use of technology. It is necessary to imp...

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Veröffentlicht in:	Sensors and materials 2022-01, Vol.34 (7), p.2637
Hauptverfasser:	Kang, Woosuk, Kim, Jisung, Yun, Hongsic, Lee, Pooreum, Kim, Heecheol
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Cameras Drone aircraft Drone vehicles Error analysis Global navigation satellite system Neural networks Object recognition Photogrammetry Sensors Unmanned aerial vehicles
Online-Zugang:	Volltext
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