Continual learning is essential for all real-world applications, as frozen pre-trained models
cannot effectively deal with non-stationary data distributions. The purpose of this study is to …

Numerous studies have adopted deep learning (DL) in financial market forecasting models
owing to its superior performance. The DL models require as many relevant input variables …

Abstract Knowledge modeling is an important step in building knowledge‐based
applications. Understanding the processes of knowledge modeling and the techniques …

This article presents an online learning method for improved control of nonlinear systems by
combining deep learning and fuzzy logic. Given the ability of deep learning to generalize …

Multirotor UAVs are used for a wide spectrum of civilian and public domain applications.
Their navigation controllers include onboard sensor suites that facilitate safe, autonomous or …

Long-term autonomy is of great importance in various real-world applications of aerial
robotics, including, but not limited to, search and rescue missions in underground mines …

To generate 3D virtual maps of outcrops in geoscience, manual flights of aerial robots are
often employed which is challenging due to various reasons: 1) piloted flight over …

Protecting the intellectual property (IP) of deep neural network (DNN) models becomes
essential and urgent with the rapidly increasing cost of DNN training. Fingerprinting is one …

The combination of artificial neural networks with advanced control techniques has shown
great potential to reject uncertainties and disturbances that affect the quadrotor during …

This paper is focused on the trajectory following problem for unmanned aerial systems in the
context of the U-space and the 4D trajectory based operations (4D-TBO). A trajectory …