Machine Learning

An industrial Ph.D. project in collaboration with ITU and Jabra

Abstract This paper explores the development of a user-friendly mobile application that combines travel planning and itinerary management. By comparing existing apps on the market and conducting user research, we identify user needs and ways to differentiate our app from competitors.

Abstract This project investigates the relationship between the occurrence of graffiti and various factors in the Amager districts of Copenhagen. The research is focused on social factors such as population density and income groups.

Abstract This thesis is a technical analysis of the weightlifting exercise deadlift, using pose detection and machine learning. Weightlifting is an increasingly popular exercise method with substantial benefits. However, if done incorrectly could lead to injuries.

Abstract This project researches whether Machine Learning (ML) and Social Media can help improve the experience for a customer who dines at restaurants. Previous studies have shown that restaurants should make their reservation and payment systems digital and online to increase customer service.

Abstract Form is essential when analyzing and reviewing a backhand disc golf throw. The form defines if the throw is performed correctly and the poses of the body define the form.

Abstract Virtual meetings and conferences are getting more common and more mainstream in the workplace. This shift in use of technology means that other work practices has to adapt to work with virtual meetings.

Abstract This thesis investigates, if an IT product can increase learning in an online setting. Information is included in regards of learning and the development of VidIT, which is an automated tracking system powered by a smartphone and an Arduino.

Abstract This project is motivated by the ever-increasing popularity of machine learning techniques for solving repetitive everyday tasks, as well as the availability and importance of smartphones in today’s society. The combination of the two creates an environment in which the use of machine learning for simplifying mundane tasks in mobile applications may be experimented with.

Abstract This thesis aims to research the question of how to predict road safety and how a driver can safely receive relevant information on road safety during a drive. This has become a relevant field of research, with sophisticated computing hardware available as a feature in cars.