Recent additions

  • A Step Towards Deep Learning-based CADs for Cancer Analysis in Medical Imaging 

    Pedersen, André (Master thesis; Mastergradsoppgave, 2019-06-01)
    In 2018, cancer was the second leading cause of death worldwide. Early detection can reduce mortality. Screening programs intended for early detection increases the workload for clinicians. To improve efficiency CAD systems would be highly beneficial. We have developed CAD systems using deep learning, for automatic tissue segmentation and prediction of diagnosis in lung and breast cancer. The ...
  • Bayesian analysis of the occurrence of myocardial infarction in the LGM framework 

    Tesfay, Yohannes Tedla (Master thesis; Mastergradsoppgave, 2019-05-21)
    The goal of this thesis is analyse the incidence rate of the first ever myocardial infarction (MI) and the survival time after the MI. The data used for this purpose is from the Troms\o{} study surveys collected in the period from 1974 to 2008. This thesis provides a general introduction to latent Gaussian models and the methodology of integrated nested Laplace approximation. Specifically, the data ...
  • Bayesian analysis of temporal and spatial trends of house prices in Norway 

    Mushore, George Sasha Tendai (Master thesis; Mastergradsoppgave, 2018-09-21)
    The goal of this thesis is to analyse the temporal and spatial trends of house prices in Norway in a Bayesian setting. We will perform regression analysis of the data which will be modelled using structured additive regression models. This choice was made because structured additive regression models can be put into a computational framework of latent Gaussian models that can be analysed using ...
  • Dirichlet process cluster kernel 

    Foslid, Tobias Olsen (Master thesis; Mastergradsoppgave, 2017-05-16)
    This thesis aims to apply the Dirichlet process mixture model to the cluster kernel framework. The probabilistic cluster kernel is extended with a Bayesian nonparametric model to avoid critical parameters within the model. The Dirichlet process cluster kernel demonstrate advantages compared to the probabilistic cluster kernel in both classification and clustering. Additionally, the two dimensional ...
  • Modelling and analysis of health care services using regression and Markov models 

    Hindenes, Lars Bakke (Master thesis; Mastergradsoppgave, 2017-05-12)
    Using data from electronic health records this thesis aims to model and analyse health care services provided to adult patients with chronic conditions. Two aspects of health care services, with unique aims, have been examined. The first aspect is related to the aim of investigating factors affecting the patients' self experienced quality of the health care encounters with regards to satisfaction, ...
  • Empirical analysis of time-lagged cross-correlations in the Norwegian Stock Market. A discussion of the Efficient Market Hypothesis 

    Jespersen, Marte (Master thesis; Mastergradsoppgave, 2016-12-15)
    In this thesis we challenge the existence of weak efficiency in the Norwegian Stock Marked, by analysing time-lagged cross-correlations between log-return series from 811 stocks listed on the Oslo stock exchange and by creating prediction strategies based on the discovered patterns. We limit the strategies to predicting the direction of the movements of the time series only, i.e. either generating ...
  • Separation of fish stocks by otoliths: Image representation, Fourier approximation and discrimination 

    Hagen, Reidar Strand (Master thesis; Mastergradsoppgave, 2015-05-18)
    In this thesis the entire process of Fourier Contour Analysis have been investigated for potential sources of bias. No potential biases has been found when creating the contour, however it has been shown there is a slight bias in which otoliths get invalidated by breakage. A probablity based sampling strategy has been suggested instead of the previously used stratification based. It has been shown ...
  • A threshold cointegration analysis of Norwegian interest rates 

    Larsen, Berner (Master thesis; Mastergradsoppgave, 2012-04)
    In this thesis we generalize the Hansen and Seo test in the R package tsDyn, which tests a linear cointegration model against a two-regime threshold cointegration model, to the case of three regimes in the alternative hypothesis. As the Lagrange Multiplier test statistic used in the Hansen and Seo test in tsDyn is different from the LM statistic described in Hansen and Seo (2002), we generalize ...
  • Applying the ICM algorithm for separating pictures consisting of two main parts, background and object application to fMRI recordings and mole pictures 

    Larsen, Are (Master thesis; Mastergradsoppgave, 2009-05-15)
    This work concentrates on using the ICM algorithm for image restoration. The algorithm has been applied to fMRI recordings and mole pictures
  • Statistical analysis of CGPS time series 

    Ouassou, Mohammed (Master thesis; Mastergradsoppgave, 2007)
    All points on the surface of the Earth are moving. To define the velocity of a given point, we can place a GPS receiver there and measure the coordinates every day. After collecting enough data, we can generate a time series of three coordinates, North, East and Height directions. The most used technique to determine such displacements, is the linear model. The main objective of this thesis ...
  • Unsupervised segmentation of skin lesions 

    Møllersen, Kajsa (Master thesis; Mastergradsoppgave, 2008-11-15)
    During the last decades, the incidence rate of cutaneous malignant melanoma, a type of skin cancer developing from melanocytic skin lesions, has risen to alarmingly high levels. As there is no effective treatment for advanced melanoma, recognizing the lesion at an early stage is crucial for successful treatment. A trained expert dermatologist has an accuracy of around 75 % when diagnosing melanoma, ...