Artificial neural network (ANN) which has four or more layers structure is called deep NN (DNN) and it is recognized as one of promising machine learning techniques. Convolutional neural network (CNN) ...

This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and edge servers’ available ...

To realize domain-invariant traffic flow pattern transfer and provide more robust prediction under insufficient data conditions, we propose a macroscopic fundamental diagram (MFD) guided transfer ...

Intelligent machine fault diagnosis methods that leverage machine learning techniques have received widespread attention owing to their proven efficacy in enhancing production efficiency and quality ...

Malware detection in Android applications remains a critical challenge due to the increasing sophistication of cyber threats. This paper explores a novel approach for Android malware classification by ...

Furthermore, incorporating transfer learning significantly reduces the dependency on extensive real-world datasets, enhancing overall model performance and facilitating future advancements in the ...

In this paper, we propose a novel framework, namely Q-TRANSFER, to address the insufficiency problem of the actual training data sets in modern networking platforms in order to push the application of ...

A brain–computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common noninvasive BCI modality, electroen ...

Deep learning has been applied in physical-layer communications systems in recent years and has demonstrated fascinating results that were comparable or even better than human expert systems. In this ...

The similarity between target and source tasks is a crucial quantity for theoretical analyses and algorithm designs in transfer learning studies. However, this quantity is often difficult to be ...

COVID-19 pandemic has revealed the need for reliable and rapid diagnostic capabilities. An image based deep transfer learning framework is proposed in current research for the detection of COVID-19 ...