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Good News AI Investigating feasibility of categorizing positive sentiment in general news
(2020-07-06)
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 ...
Convolutions on graphs for learning vehicle crash behaviour
(2021-11-09)
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 ...
Learning Geometry Compatibility with 3D Convolutional Neural Networks
(2019-10-04)
Modern video games offer substantial amounts of customization options. Manually testing the visual compatibility of all options is time-consuming and error-prone. Together with Ghost Games, we present a method of learning ...
Evaluating trace link visualizations
(2021-03-03)
Traceability has become a very important part of the software development lifecycle and
therefor a lot of research has been done and is being done about it. Our aim with this
paper is to explore and evaluate the effect ...
Automated Metadata Extraction for Job Advertisements
(2022-06-20)
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 ...
A type-driven approach for sensitivity checking with branching
(2023-10-24)
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 ...