With outstanding features, machine learning (ML) has become the backbone of numerous
applications in wireless networks. However, the conventional ML approaches face many …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

With outstanding features, Machine Learning (ML) has been the backbone of numerous
applications in wireless networks. However, the conventional ML approaches have been …

Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …

This study proposed a new processing method to predict breast cancer on the basis of nine
individual attributes, including age, body mass index, glucose, insulin, and a homeostasis …

Spectrum sensing is an efficient technology for addressing the shortage of spectrum
resources. Widely used methods usually employ model‐based features as the test statistics …

Transfer learning is a pervasive technology in computer vision and natural language
processing fields, yielding exponential performance improvements by leveraging prior …

The exponential growth of Internet connected systems has generated numerous challenges,
such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions …

The detection of primary user signals is essential for optimum utilization of a spectrum by
secondary users in cognitive radio (CR). The conventional spectrum sensing schemes have …

In this article, we propose a transfer learning (TL) enabled edge convolutional neural
network (CNN) framework for 5G industrial edge networks with privacy-preserving …