… Deep learning,a machine-learning method characterized by … the brain called artificial neural
networks,has shown exceptional … a method for the individual identification of drone radiation …

… , unmanned aerial vehicles for … deep-neural-network-based recognition models for
multiple-source remote sensing images. First, we discuss the incompleteness of deep learning …

… , this thesis has two main objective utilizing wireless networks. … indicate that unmanned
aerial vehicles (UAVs) significantly … are mainly machine learning-based solutions that mostly …

… vector machine classification exceed 90%, while the overall accuracy of deep learning method
is only 84%. In terms of … Key words:unmanned aerial vehicle image;urban vegetation;fine …

… In this work, we present UH-Sense, the first unmanned aerial vehicle (UAV) based human …
the UAV is used to measure the signal strength from the surrounding WiFi access points (APs). …

… -A) is the mainstream mobile network used by the general public. … points of mobile devices
based on machine learning. … the use of drones as RNs in the LTE-A network environment, …

… a machine learning method that combines deep learning (DL) and reinforcement learning
(… A saliency-based reinforcement learning approach for a UAV to avoid flying obstacles. …

… This may lead to UANET service performance issues. In this … UAV swarms, we propose a
dynamic value iteration network (DVIN) model trained using the episodic Q-learning method …

… a UAV mission by the US Department of Transportation; the 15 m is the empirically determined
lowest above ground level for a UAV mission based … performance of the machine learning …

… (Automatic H-shaped steel coating thickness classification using deep convolution neural
network) … International workshop on machine learning and data mining in pattern recognition, …