Transfer learning promotes 6G wireless communications: Recent advances and future challenges

M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …

Deep learning based automatic modulation recognition: Models, datasets, and challenges

F Zhang, C Luo, J Xu, Y Luo, FC Zheng - Digital Signal Processing, 2022 - Elsevier
Automatic modulation recognition (AMR) detects the modulation scheme of the received
signals for further signal processing without needing prior information, and provides the …

[HTML][HTML] Large-scale real-world radio signal recognition with deep learning

TU Ya, LIN Yun, ZHA Haoran, J Zhang, W Yu… - Chinese Journal of …, 2022 - Elsevier
In the past ten years, many high-quality datasets have been released to support the rapid
development of deep learning in the fields of computer vision, voice, and natural language …

Fuzzy detection aided real-time and robust visual tracking under complex environments

S Liu, S Wang, X Liu, CT Lin, Z Lv - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Today, a new generation of artificial intelligence has brought several new research domains
such as computer vision (CV). Thus, target tracking, the base of CV, has been a hotspot …

An efficient specific emitter identification method based on complex-valued neural networks and network compression

Y Wang, G Gui, H Gacanin, T Ohtsuki… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Specific emitter identification (SEI) is a promising technology to discriminate the individual
emitter and enhance the security of various wireless communication systems. SEI is …

Threat of adversarial attacks on DL-based IoT device identification

Z Bao, Y Lin, S Zhang, Z Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the rapid development of the information technology, the number of devices in the
Internet of Things (IoT) is increasing explosively, which makes device identification a great …

Machine and deep learning for resource allocation in multi-access edge computing: A survey

H Djigal, J Xu, L Liu, Y Zhang - IEEE Communications Surveys …, 2022 - ieeexplore.ieee.org
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

Machine learning based bearing fault diagnosis using the case western reserve university data: A review

X Zhang, B Zhao, Y Lin - Ieee Access, 2021 - ieeexplore.ieee.org
The most important parts of rotating machinery are the rolling bearings. Finding bearing
faults in time can avoid affecting the operation of the entire equipment. The data-driven fault …

GLR-SEI: green and low resource specific emitter identification based on complex networks and fisher pruning

Y Lin, H Zha, Y Tu, S Zhang, W Yan… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Better neural networks, more powerful computer hardware and signal Big Data make deep
learning increasingly important in Specific Emitter Identification (SEI). However, its …

Blockchain assisted secure data sharing model for Internet of Things based smart industries

G Manogaran, M Alazab, PM Shakeel… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Industrial Internet of Things is focused to improve the performance of smart factories through
automation and scalable functions. IoT paradigm, information and communication …