Structural crack detection using deep convolutional neural networks

R Ali, JH Chuah, MSA Talip, N Mokhtar… - Automation in …, 2022 - Elsevier
Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …

Deep learning in mobile and wireless networking: A survey

C Zhang, P Patras, H Haddadi - IEEE Communications surveys …, 2019 - ieeexplore.ieee.org
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

Future intelligent and secure vehicular network toward 6G: Machine-learning approaches

F Tang, Y Kawamoto, N Kato, J Liu - Proceedings of the IEEE, 2019 - ieeexplore.ieee.org
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …

Ten challenges in advancing machine learning technologies toward 6G

N Kato, B Mao, F Tang, Y Kawamoto… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
As the 5G standard is being completed, academia and industry have begun to consider a
more developed cellular communication technique, 6G, which is expected to achieve high …

Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges

F Tang, B Mao, N Kato, G Gui - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

Deep learning for super-resolution channel estimation and DOA estimation based massive MIMO system

H Huang, J Yang, H Huang, Y Song… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The recent concept of massive multiple-input multiple-output (MIMO) can significantly
improve the capacity of the communication network, and it has been regarded as a …

Deep learning for intelligent wireless networks: A comprehensive survey

Q Mao, F Hu, Q Hao - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …

Spectrum interference-based two-level data augmentation method in deep learning for automatic modulation classification

Q Zheng, P Zhao, Y Li, H Wang, Y Yang - Neural Computing and …, 2021 - Springer
Automatic modulation classification is an essential and challenging topic in the development
of cognitive radios, and it is the cornerstone of adaptive modulation and demodulation …

Networking and communications in autonomous driving: A survey

J Wang, J Liu, N Kato - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
The development of light detection and ranging, Radar, camera, and other advanced sensor
technologies inaugurated a new era in autonomous driving. However, due to the intrinsic …

Deep-learning-based millimeter-wave massive MIMO for hybrid precoding

H Huang, Y Song, J Yang, G Gui… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has been
regarded to be an emerging solution for the next generation of communications, in which …