Blar i Institutt for datateknologi og informatikk på tittel
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Learning and Evolution in Complex Fitness Landscapes
(Master thesis, 2007)The Baldwin effect is the notion that life time adaptation can speed up evolution by 1) identifying good traits and 2) by genetic assimilation inscribing the traits in the population genetically. This thesis investigates ... -
Learning Automata with Artificial Reflecting Barriers in Games with Limited Information
(Journal article, 2022)This paper deals with the problem of solving stochastic games (which have numerous business and economic applications), using the interesting tools of Learning Automata (LA), the precursors to Reinforcement Learning (RL). ... -
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation
(Peer reviewed; Journal article, 2023)Purpose This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. Methods Different training strategies, loss functions, and ... -
Learning Distance Functions in k-Nearest Neighbors
(Master thesis, 2013)Normally the distance function used in classification in the k-Nearest Neighbors algorithm is the euclidean distance. This distance function is simple and has been shown to work on many different datasets. We propose a ... -
Learning event-driven time series with phased recurrent neural networks
(Master thesis, 2018)We explore machine learning algorithms for time series data, particularly recurrent neural networks. For us, the most interesting methods are ones for handling long duration time series, where the sampling of data channels ... -
Learning exact enumeration and approximate estimation in deep neural network models
(Journal article; Peer reviewed, 2021)A system for approximate number discrimination has been shown to arise in at least two types of hierarchical neural network models—a generative Deep Belief Network (DBN) and a Hierarchical Convolutional Neural Network ... -
Learning from COVID-19 emergency remote teaching: A case study to compare pupil and teacher experiences
(Master thesis, 2021)Den norske regjeringen besluttet den 12. mars 2020 å stenge alle skoler på grunn av COVID-19-pandemien. Skolestengingene førte til store forstyrrelser i de norske utdanningssystemene, da skolene ble tvunget til å finne ... -
Learning from COVID-19 emergency remote teaching: A case study to compare pupil and teacher experiences
(Master thesis, 2021)Den norske regjeringen besluttet den 12. mars 2020 å stenge alle skoler på grunn av COVID-19-pandemien. Skolestengingene førte til store forstyrrelser i de norske utdanningssystemene, da skolene ble tvunget til å finne ... -
Learning How to Program With a Self Evaluation System - A Study on Motivational Aspects and Learning Effect
(Master thesis, 2017)Learning how to program is difficult for many students, as it separates itself from many of the traditional technological fields like mathematics, chemistry, and physics. Additionally, many students have never programmed ... -
Learning Image Relations with Contrast Association Networks
(Chapter, 2019)Inferring the relations between two images is an important class of tasks in computer vision. Examples of such tasks include computing optical flow and stereo disparity. We treat the relation inference tasks as a machine ... -
Learning impact evaluation of peer learning and immersion in AR
(Master thesis, 2023)ABSTRAKT I dag, med teknologi som en viktig del av ulike områder av menneskelivet, er det nødvendig å foreta en omfattende vurdering av teknologiens innvirkning på brukeropplevelsen på anvendelsesområdet. Utdanning er et ... -
Learning in Cities from Within and Across Cities: A Scoping Review
(Peer reviewed; Journal article, 2023)Cities evolve rapidly while providing both opportunities and posing challenges. To cope with the emerging behaviours of cities, contextual innovations and development are essential. Driving innovations through the learning ... -
Learning in Smart Environments: User-centered Design and Analytics of an Adaptive Learning System
(Journal article; Peer reviewed, 2018)The complexity of today’s learning processes and practices entails various challenges. It is becoming much harder for teachers to observe, control, and adjust the learning process. Moreover, contemporary teaching is enhanced ... -
Learning in the Large - An Exploratory Study of Retrospectives in Large-Scale Agile Development
(Journal article; Peer reviewed, 2018)Many see retrospectives as the most important practice of agile software development. Previous studies of retrospectives have focused on pro- cess and outcome at team level. In this article, we study how a large-scale agile ... -
Learning More for Free-A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
(Chapter, 2021)The progress in Computer Aided Diagnosis (CADx) of Wireless Capsule Endoscopy (WCE) is thwarted by the lack of data. The inadequacy in richly representative healthy and abnormal conditions results in isolated analyses of ... -
Learning multi-granularity dynamic network representations for social recommendation
(Journal article; Peer reviewed, 2019)With the rapid proliferation of online social networks, personalized social recommendation has become an important means to help people discover useful information over time. However, the cold-start issue and the special ... -
Learning neural representations for the processing of temporal data in deep neutral networks
(Doctoral theses at NTNU;2023:6, Doctoral thesis, 2023)Ever since the third spring of artificial intelligence a decadeago, representation learning through deep neural networks hasbeen the dominating approach for most research in machinelearning. However, typical deep neural ... -
Learning pattern models from examples
(Master thesis, 2006)The aim of this thesis is twofold. Firstly, it is a survey of some of the most prevalent pattern models used in motif discovery algorithms. The main goal of the survey is to see how well these models with all their ... -
Learning robot soccer with UCT
(Master thesis, 2008)Upper Confidence bounds applied to Trees, or UCT, has shown promise for reinforcement learning problems in different kinds of games, but most of the work has been on turn based games and single agent scenarios. In this ... -
Learning similarity measures from data
(Journal article; Peer reviewed, 2019)Defining similarity measures is a requirement for some machine learning methods. One such method is case-based reasoning (CBR) where the similarity measure is used to retrieve the stored case or a set of cases most similar ...