In today’s society we are constantly fed information about catastrophic or sad events through media. While it is important to know about these events, it should be equally important to also see all the good things that ...

Convolutional Neural Networks (CNN) have shown successful results in the recent years, especially within the area of image analysis. The idea of learning to predict the result of a crash simulation using machine learning ...

This thesis is written in collaboration with the Swedish Public Employment Service and aims to investigate methods and techniques to automatically extract metadata from unstructured texts. The Swedish Public Employment ...

This thesis aims to answer whether it is possible to produce one or more baselines based on naturalistic driving data collected over a period of 8 months. The baseline is based on variables extracted from the drivers ...

In the field of medical science datasets are often highly imbalanced, where rare datapoints are of high importance. This study aims to explore the usage of synthetic datasets to improve the classification of echocardiogram ...

Differential Privacy (DP) is a promising approach to allow privacy preserving statistics over large datasets of sensitive data. It works by adding random noise to the result of the analytics. Understanding the sensitivity ...

Traditional Internet of things systems suffer from limitations inherent to the clientserver architecture, with the entire system being dependant on the correct functionality of the server. Alternative decentralized ...