79 citations · 186 across the 19 of their papers we have counts for
19 papers
Underwater Acoustic Communication Channel Modeling using Reservoir Computing
Oluwaseyi Onasami, Ming Feng, Hao Xu +2
Underwater acoustic (UWA) communications have been widely used but greatly impaired due to the complicated nature of the underwater environment. In order to improve UWA communicati…
Underwater Acoustic Communication Channel Modeling using Deep Learning
Oluwaseyi Onasami, Damilola Adesina, Lijun Qian
With the recent increase in the number of underwater activities, having effective underwater communication systems has become increasingly important. Underwater acoustic communicat…
A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks
Bo Yang, Omobayode Fagbohungbe, Xuelin Cao +4
In this paper, we propose a transfer learning (TL)-enabled edge-CNN framework for 5G industrial edge networks with privacy-preserving characteristic. In particular, the edge server…
Semi-supervised Learning for COVID-19 Image Classification via ResNet
Lucy Nwosu, Xiangfang Li, Lijun Qian +2
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic in over 200 countries and territories, which has resulted in a great public health concern across the internationa…
Intelligent Spectrum Learning for Wireless Networks with Reconfigurable Intelligent Surfaces
Bo Yang, Xuelin Cao, Chongwen Huang +3
Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired sign…
A Survey of Complex-Valued Neural Networks
Joshua Bassey, Lijun Qian, Xianfang Li
Artificial neural networks (ANNs) based machine learning models and especially deep learning models have been widely applied in computer vision, signal processing, wireless communi…
Benchmarking Inference Performance of Deep Learning Models on Analog Devices
Omobayode Fagbohungbe, Lijun Qian
Analog hardware implemented deep learning models are promising for computation and energy constrained systems such as edge computing devices. However, the analog nature of the devi…
Edge Intelligence for Autonomous Driving in 6G Wireless System: Design Challenges and Solutions
Bo Yang, Xuelin Cao, Kai Xiong +5
In a level-5 autonomous driving system, the autonomous driving vehicles (AVs) are expected to sense the surroundings via analyzing a large amount of data captured by a variety of o…
Adversarial Machine Learning in Wireless Communications using RF Data: A Review
Damilola Adesina, Chung-Chu Hsieh, Yalin E. Sagduyu +1
Machine learning (ML) provides effective means to learn from spectrum data and solve complex tasks involved in wireless communications. Supported by recent advances in computationa…
Offloading Optimization in Edge Computing for Deep Learning Enabled Target Tracking by Internet-of-UAVs
Bo Yang, Xuelin Cao, Chau Yuen +1
The empowering unmanned aerial vehicles (UAVs) have been extensively used in providing intelligence such as target tracking. In our field experiments, a pre-trained convolutional n…
Computation Offloading in Multi-Access Edge Computing Networks: A Multi-Task Learning Approach
Bo Yang, Xuelin Cao, Joshua Bassey +3
Multi-access edge computing (MEC) has already shown the potential in enabling mobile devices to bear the computation-intensive applications by offloading some tasks to a nearby acc…
Lessons Learned from Accident of Autonomous Vehicle Testing: An Edge Learning-aided Offloading Framework
Bo Yang, Xuelin Cao, Xiangfang Li +2
This letter proposes an edge learning-based offloading framework for autonomous driving, where the deep learning tasks can be offloaded to the edge server to improve the inference…
Cell Type Identification from Single-Cell Transcriptomic Data via Semi-supervised Learning
Xishuang Dong, Shanta Chowdhury, Uboho Victor +2
Cell type identification from single-cell transcriptomic data is a common goal of single-cell RNA sequencing (scRNAseq) data analysis. Neural networks have been employed to identif…
Efficient Privacy Preserving Edge Computing Framework for Image Classification
Omobayode Fagbohungbe, Sheikh Rufsan Reza, Xishuang Dong +1
In order to extract knowledge from the large data collected by edge devices, traditional cloud based approach that requires data upload may not be feasible due to communication ban…
Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media
Chandra Mouli Madhav Kotteti, Xishuang Dong, Lijun Qian
Social media is a popular platform for timely information sharing. One of the important challenges for social media platforms like Twitter is whether to trust news shared on them w…
Device Authentication Codes based on RF Fingerprinting using Deep Learning
Joshua Bassey, Xiangfang Li, Lijun Qian
In this paper, we propose Device Authentication Code (DAC), a novel method for authenticating IoT devices with wireless interface by exploiting their radio frequency (RF) signature…
Two-path Deep Semi-supervised Learning for Timely Fake News Detection
Xishuang Dong, Uboho Victor, Lijun Qian
News in social media such as Twitter has been generated in high volume and speed. However, very few of them are labeled (as fake or true news) by professionals in near real time. I…
Deep Two-path Semi-supervised Learning for Fake News Detection
Xishuang Dong, Uboho Victor, Shanta Chowdhury +1
News in social media such as Twitter has been generated in high volume and speed. However, very few of them can be labeled (as fake or true news) in a short time. In order to achie…
Hierarchical Transfer Convolutional Neural Networks for Image Classification
Xishuang Dong, Hsiang-Huang Wu, Yuzhong Yan +1
In this paper, we address the issue of how to enhance the generalization performance of convolutional neural networks (CNN) in the early learning stage for image classification. Th…