Artificial neural networks-based machine learning for wireless networks: A tutorial

M Chen, U Challita, W Saad, C Yin… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
In order to effectively provide ultra reliable low latency communications and pervasive
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …

[PDF][PDF] Machine learning for wireless networks with artificial intelligence: A tutorial on neural networks

M Chen, U Challita, W Saad, C Yin… - arXiv preprint arXiv …, 2017 - researchgate.net
Next-generation wireless networks must support ultra-reliable, low-latency communication
and intelligently manage a massive number of Internet of Things (IoT) devices in real-time …

Convergence of machine learning and robotics communication in collaborative assembly: mobility, connectivity and future perspectives

SH Alsamhi, O Ma, MS Ansari - Journal of Intelligent & Robotic Systems, 2020 - Springer
Collaborative assemblies of robots are promising the next generation of robot applications
by ensuring that safe and reliable robots work collectively toward a common goal. To …

Jamming detection and classification in OFDM-based UAVs via feature-and spectrogram-tailored machine learning

Y Li, J Pawlak, J Price, K Al Shamaileh, Q Niyaz… - IEEE …, 2022 - ieeexplore.ieee.org
In this paper, a machine learning (ML) approach is proposed to detect and classify jamming
attacks against orthogonal frequency division multiplexing (OFDM) receivers with …

Intelligent collaborative navigation and control for AUV tracking

J Guo, D Li, B He - IEEE Transactions on Industrial Informatics, 2020 - ieeexplore.ieee.org
In order to maintain the submarine equipment, autonomous underwater vehicle (AUV) is
usually assigned to track the submarine cables or pipes. The capabilities of navigation and …

Experimental kinematic modeling of 6-dof serial manipulator using hybrid deep learning

NA Mohamed, AT Azar, NE Abbas, MA Ezzeldin… - Proceedings of the …, 2020 - Springer
According to its significance, robotics is always an area of interest for research and further
development. While robots have varying types, design and sizes, the six degrees of freedom …

Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs

VAMF Torres, BRA Jaimes, ES Ribeiro… - … Applications of Artificial …, 2020 - Elsevier
This work presents a combined weightless neural network architecture for deforestation
surveillance and visual navigation of Unmanned Aerial Vehicles (UAVs). Binary images …

Autonomous navigation and landing of large jets using artificial neural networks and learning by imitation

H Baomar, PJ Bentley - 2017 IEEE symposium series on …, 2017 - ieeexplore.ieee.org
We introduce the Intelligent Autopilot System (IAS) which is capable of autonomous
navigation and landing of large jets such as airliners by observing and imitating human …

A comprehensive review on the use of AI in UAV communications: Enabling technologies, applications, and challenges

F Al-Turjman, H Zahmatkesh - Unmanned Aerial Vehicles in Smart Cities, 2020 - Springer
Artificial intelligence (AI) has a great capability to deal with big data and complexity as well
as speedy and high-accuracy processing. AI algorithms along with robotics can be used to …

A machine learning approach for detecting and classifying jamming attacks against ofdm-based uavs

J Pawlak, Y Li, J Price, M Wright… - Proceedings of the 3rd …, 2021 - dl.acm.org
In this paper, a machine learning (ML) approach is proposed to detect and classify jamming
attacks on unmanned aerial vehicles (UAVs). Four attack types are implemented using …