Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …

Research on intelligent vehicles has been popular in the past decade. To fill the gap
between automatic approaches and man-machine control systems, it is indispensable to …

Recently, artificial intelligence (AI) techniques have been used to describe the
characteristics of information, as they help in the process of data mining (DM) to analyze …

Urban anomalies may result in loss of life or property if not handled properly. Automatically
alerting anomalies in their early stage or even predicting anomalies before happening is of …

One major cause of performance degradation in predictive models is that the test samples
are not well covered by the training data. Such not well-represented samples are called OoD …

Interactive machine learning (IML) is an iterative learning process that tightly couples a
human with a machine learner, which is widely used by researchers and practitioners to …

As the Internet of Things (IoT) grows rapidly, huge amounts of wireless sensor networks
emerged monitoring a wide range of infrastructure, in various domains such as healthcare …

This paper addresses the taxi fraud problem and introduces a new solution to identify
trajectory outliers. The approach as presented allows to identify both individual and group …