Abstract Cyber attacks on Industrial Control Systems (ICSs) to disrupt the associated
physical systems, like power grids and water treatment plants, are a harsh reality of the …

Random forest classification is a well known machine learning technique that generates
classifiers in the form of an ensemble (" forest") of decision trees. The classification of an …

Classification is one of the most important techniques to the analysis of hyperspectral remote
sensing images. Nonetheless, there are many challenging problems arising in this task. Two …

In a typical smart city, drones can collect (or sense) massive amount of data, that is sent to a
computing capability for further analysis to make useful decision making without human …

In recent years, machine learning algorithms have been used in many areas, from high-
performance to edge computing. As one of the most attractive machine learning algorithms …

A decision tree is a well-known machine learning technique. Recently their popularity has
increased due to the powerful Gradient Boosting ensemble method that allows to gradually …

With increasing capabilities of energy efficient systems, computational technology can be
deployed, virtually everywhere. Machine learning has proven a valuable tool for extracting …

Decision tree classification (DTC) is a widely used technique in data mining algorithms
known for its high accuracy in forecasting. As technology has progressed and available …

Abstract Field Programmable Gate Arrays (FPGAs) are integrated circuits that can be
configured by the user after manufacturing, making them suitable for customized hardware …

We present a novel implementation of classification using the machine learning/artificial
intelligence method called boosted decision trees (BDT) on field programmable gate arrays …