• Expanding Convolutional Tsetlin Machine for Images with Lossless Binarization 

  Håsæther, Jens Martin (Master thesis, 2020)

  Deep convolutional neural networks (CNN) is known to be efficient in image classification but non-interpretable. To overcome the black box nature of CNN a derivative of the Tsetlin automata, the convolutional Tsetlin machine ...

• Learning Automata-Based Object Partitioning with Pre-Specified Cardinalities 

  Omslandseter, Rebekka Olsson (Master thesis, 2020)

  The Object Migrating Automata (OMA) has been used as a powerful AI-based tool to resolve real-life partitioning problems. Apart from its original version, variants and enhancements that invoke the pursuit concept ...

• 3D Convolution Neural Networks for Medical Imaging; Classification and Segmentation : A Doctor’s Third Eye 

  Giri, Charul (Master thesis, 2020)

  In this thesis, we studied and developed 3D classification and segmentation models for medical imaging. The classification is done for Alzheimer’s Disease and segmentation is for brain tumor sub-regions. For the medical ...

• The user experience approach to Augmented Reality design, providing ADL support for the mentally disabled 

  Lende, Einar (Master thesis, 2020)

• An Encoder-Decoder based Deep Learning Approach for Anonymization of Visual Surveillance Media with Preservation of Utility 

  Lindseth, Eivind (Master thesis, 2020)

  The field of computer vision has seen significant progress recently fol-lowing innovations in deep learning neural networks. Activity can be identified from surveillance cameras. Automatic detection of unwanted incidents ...

• A Deep Learning-based approach for Fault Detection of Power Lines 

  Mathisen, Christer (Master thesis, 2020)

  A transmission network is the most crucial part of modern infrastructure. However, it requires an extensive amount of power line inspection each year to maintain, and with an increased interest in replacing large ...

• Predicting Electrical Power Consumption on Yearly Events for Substations: Algorithm Design and Performance Evaluations 

  Langemyr, Adrian (Master thesis, 2020)

  Accurate prediction of electricity usage is critical for grid companies in or-der to ensure reliable power supply for their customers. Many factors in-fluence usage patterns, but generally they consist of yearly-, ...

• Analysis of binarization techniques and Tsetlin machine architectures targeting image classification 

  Mathisen, Erik; Smørvik, Halvor S. (Master thesis, 2020)

  The Tsetlin Machine is a constantly evolving and developing machine learning technique with ever-increasing success. However, for every success, the Tsetlin Machine achieves, a new set of challenges are put ahead. ...

• TsetlinGo : Solving the game of Go with Tsetlin Machine 

  Magelssen, Kristoffer Lomeland; Storebø, Trond (Master thesis, 2020)

  The Tsetlin Machine have already shown great promise on pattern recognition and text categorization. The board game GO is a highly complex game, and the Tsetlin Machine have not yet been tested extensively on strategic ...

• Playing endgame chess with the Tsetlin Machine 

  Otterlei, Sander J.; Reiersøl, Joel A. H. (Master thesis, 2020)

  The report is about training an Artificial Intelligence(AI) that is able to play out endgames, using the existing solved endgame of chess to train the Tsetlin Machine on. This report describes the methods used to ...

• A Machine Learning Approach for Intrusion Detection 

  Abohaikel, Amir Sadiq; Tokheim, Erik (Master thesis, 2020)

  Securing networks and their confidentiality from intrusions is crucial, and for this rea-son, Intrusion Detection Systems have to be employed. The main goal of this thesis is to achieve a proper detection performance of a ...

• The Application of the Tsetlin Machine in Checkers 

  Bråten, Martin (Master thesis, 2020)

  The Tsetlin Machine has shown promising results in the domain of board games such as Axis& Allies, showing that the Tsetlin Machine may be a contender to more well-known machine learning algorithms. This research aimed ...

• Generating Levels and Playing Super Mario Bros. with Deep Reinforcement Learning Using various techniques for level generation and Deep Q-Networks for playing 

  Engelsvoll, Ruben Nygård; Gammelsrød, Anders; Thoresen, Bjørn-Inge Støtvig (Master thesis, 2020)

  This thesis aims to explore the behavior of two competing reinforcement learning agents in Super Mario Bros. In video games, PCG can be used to assist human game designers by generating a particular aspect of the game. A ...

• Design and Implementation of Self-Powered Long Range IoT Device Based on LoRaWAN 

  Bhusal, Hari (Master thesis, 2020)

  This project proposes a self-powered long-range wireless sensor node based on Long Range Wide Area Network (LoRaWAN) with various sensing capabilities. The nodes have been designed in such a way that these are ...

• Hierarchical Fish Species Detection in Real-Time Video Using YOLO 

  Kalhagen, Espen Stausland; Olsen, Ørjan Langøy (Master thesis, 2020)

  Information gathering of aquatic life is often based on time consuming methods with a foundation in video feeds. It would be beneficial to capture more information in a cost effective manner from video feeds, ...

• A Generative Adversarial Network approach using Latent Space Manipulation for Clothing Display on Synthetic Images Using the latent space of an non-primed StyleGAN2 networkto manipulate arbitrary clothing onto generated humans 

  Borgersen, Karl Audun; Grundetjern, Morten (Master thesis, 2020)

  The Fashion industry is continuously inventing new clothing. A significant bottleneck when introducing newly designed clothing to the market is advertisements. This thesis looks into the possibility of streamlining this ...

• Playing the game of Hex with theTsetlin Machine and tree search 

  Simonsen, Audun Linjord; Haddeland, Ole André (Master thesis, 2020)

  Hex is an abstract mathematical board game where the players aim to build a connection of pieces, traversing the board from edge to edge. The game requires the use of certain patterns to be played ...

• Imitation Accelerated Q-learning on a Simulated Formula Student Driverless Racecar 

  Ellingsen, Nikolai Kjærem (Master thesis, 2020)

  In the international Formula Student competition, only a handful compete in the driverless category. Most of them using expensive hardware such as LIDAR’s. By leveraging reinforcement learning, a cheaper camera based ...

• "De er jo her fysisk. Da kan de jo bare snakke med hverandre." : En kvalitativ studie av hvilke faktorer som påvirker samfunnsfaglæreres tilrettelegging for elevenes bruk av digital samhandling og kommunikasjon på ungdomstrinnet 

  Midtlund, Arne (Master thesis, 2020)

  Dette forskningsprosjektet har hatt som formål å undersøke hvilke faktorer som påvirker lærere på ungdomstrinnet når de planlegger for elevenes bruk av digitale verktøy til samarbeid og kommunikasjon. Forskningsspørsmålene ...

• Investigating a Virtual Reality Solution for Rehabilitation in a Biomechatronics Lab and Home Environment 

  Madshaven, Julie Madelen; Markseth, Tonje Fjeldstad (Master thesis, 2020)

  Virtual reality (VR) has emerged as a promising technical tool in physical rehabilitation. VR rehabilitation (VRR) programs, like any rehabilitation, attempt to promote neuroplasticity to improve physical rehabilitation. ...

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