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Backward stochastic differential equations with applications
(2018)
In this thesis we study backward stochastic differential equations driven by a Brownian motion and by a Levy process and their applications, focusing on their applications to financial markets. We give results on the ...
Hand tracking with sub-pixel precision
(2020)
Human-Computer Interaction has matured from simple keyboard and mouse interface to touch screens, and more recently to 3-D touch screen interfaces. Recently, high precision object tracking algorithms are being deployed for ...
Sequential estimation of state-space model parameters
(2021)
Sequential Monte Carlo or particle filtering is a class of methods to approximate distributions of interest sequentially as new observations arrive. The potential of particle filtering in a parameter estimation context ...
Mathematical modelling of malaria based on Uganda data
(2018)
Malaria infection remains a major health burden in many parts of the world, especially sub-Saharan Africa. Long lasting insecticide nets (LLIN) and indoor residual sprays (IRS) are the most recommended malaria control ...
Silicon PIN-diodes with gate induced passivation : fabrication and characterisation
(2021)
Silicon PIN diode has been common and efficient configuration for detector purposes for long time. In order to reduce the dead layer on top of the detector, PIN diodes with induced passivation were fabricated and characterised. ...
Effect of humidity on electric potential of SnO2 film investigated by Kelvin probe force microscopy
(2020)
In this study hygroelectric behaviour of an SnO2 sample was studied using Kelvin probe force microscopy (KPFM) and humidity controlling equipment. The objective was to detect any possible surface potential changes within ...
Learned image reconstruction in X-ray computed tomography
(2020)
The basic idea behind X-ray computed tomography (CT) is, given the change in the intensities of X-ray beams passing through a target object, to reconstruct the image of the object's density that is characterized by the ...
Hamiltonian Monte Carlo and non-Gaussian random field priors for x-ray tomography
(2019)
Solving a statistical inverse problem requires selecting an appropriate prior distribution to model the phenomenon in question and using numerical algorithms, like MCMC methods, to calculate the estimates in practise. ...
Improving the performance of Bayesian deep model training for artery-vein segmentation
(2020)
Retinal images are an important tool for diagnosis of ocular diseases. Automating the process of screening the retinal images would allow wider screening and make diagnosing of patients’ swifter. The possibility of performing ...
Predicting imbalance power price
(2021)
The electricity market is a complex multi-layer system that is designed to balance power consumption and production at every single moment. This thesis focuses on the lowest level of the Finnish electricity market called ...