Browsing Brage NMBU by Author "Tomic, Oliver"
Now showing items 1-20 of 65
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30-dagers reinnleggelse av eldre 2011–2013. Resultater for sykehus og kommuner
Lindman, Anja Schou; Kristoffersen, Doris Tove; Hassani, Sahar; Tomic, Oliver; Helgeland, Jon (Research report, 2015) -
Analysis of proteins from cerebrospinal fluid tests in search of biomarkers characterizing Multiple sclerosis
El-Hajj Eid, Karim (Master thesis, 2020)There are contradicting theories describing Multiple sclerosis (MS). This study attempts to understand MS through interpreting the bio-markers of MS. Recursive feature elimination with cross validation (RFECV) was used to ... -
Application of sequential and orthogonalised-partial least squares (SO-PLS) regression to predict sensory properties of Cabernet Sauvignon wines from grape chemical composition
Niimi, Jun; Tomic, Oliver; Næs, Tormod; Jeffery, David; Bastian, Susan E.P.; Boss, Paul K. (Journal article; Peer reviewed, 2018) -
Assessment of machine learning methods for automatic tumor segmentation
Grøndahl, Aurora Rosvoll (PhD Thesis;2023:12, Doctoral thesis, 2023)The definition of target volumes and organs at risk (OARs) is a critical part of radiotherapy planning. In routine practice, this is typically done manually by clinical experts who contour the structures in medical images ... -
Automated redaction of historical documents using machine learning
Hetland, Petter Kolstad; Sigerstad, Tomas (Master thesis, 2021)This thesis aims to assist Arkivverket, The National Archival Services of Norway, in automating the redaction of national identity numbers in historical documents. As historical documents are released to the public at ... -
Automated volumetric delineation of cancer tumors on PET/CT images using 3D convolutional neural network (V-Net)
Mirza, Afreen (Master thesis, 2020)The process of delineation of tumors and malignant lymph nodes using medical images is a fundamental part of radiotherapy planning. Still, this process is done manually by radiologists. This process is time-consuming and ... -
Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning
Grøndahl, Aurora Rosvoll; Huynh, Bao Ngoc; Tomic, Oliver; Søvik, Åste; Dale, Einar; Malinen, Eirik; Skogmo, Hege Kippenes; Futsæther, Cecilia Marie (Peer reviewed; Journal article, 2023) -
Comparative study of NER using Bi-LSTM-CRF with different word vectorisation techniques on DNB documents
Joseph, Meera (Master thesis, 2021)The presence of huge volumes of unstructured data in the form of pdf documents poses a challenge to the organizations trying to extract valuable information from it. In this thesis, we try to solve this problem as per the ... -
Computer vision for surface analysis of stretch wrapped pallets
Dramstad, Morten (Master thesis, 2020)The majority of the handling of goods in a distribution center is performed automatically, except removing of stretch film from arriving pallets. The use of cameras and artificial intelligence to analyze the pallets, decide ... -
Data- and expert-driven feature selection for predictive models in healthcare : towards increased interpretability in underdetermined machine learning problems
Jenul, Anna Selina (PhD Thesis;2023:34, Doctoral thesis, 2023)Modern data acquisition techniques in healthcare generate large collections of data from multiple sources, such as novel diagnosis and treatment methodologies. Some concrete examples are electronic healthcare record systems, ... -
Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients
Moe, Yngve Mardal; Grøndahl, Aurora Rosvoll; Tomic, Oliver; Dale, Einar; Malinen, Eirik; Futsæther, Cecilia Marie (Peer reviewed; Journal article, 2021) -
Detection and quantification of rot in harvested trees using convolutional neural networks
Nowell, Tyrone Carlisle (Master thesis, 2019)Root and Butt-Rot (RBR) is having a significant economic impact on the forest industry and is expected to increase with climate change. The current management strategies are becoming less effective, and little data on ... -
Development of a user-friendly radiomics framework
Albuni, Ahmed (Master thesis, 2020)The goal of this thesis is to implement an easy to use, user-friendly application to help researchers in the field of radiomics and image processing to extract radiomics features. The application also includes an easy way ... -
Diagnosing patients with Major Depressive Disorder using radiomics features extracted from MR scans of the brain
Tukun, Kristin (Master thesis, 2021)The main aim of this study was to diagnose patients with major depressive disorder (MDD) using structural T1 weighted images of the brain. The images originate from the DELHI study conducted in the Netherlands ... -
Differences between generalised procrustes analysis and multiple factor analysis in case of projective mapping
Tomic, Oliver (Master thesis, 2014-02-13)Raske sensoriske metoder har blitt veldig populære i matvitenskap og spesielt i internasjonal matindustri. De er appelerende fordi de er kostnadseffektive og raskere å gjennomføre enn noen av de tradisjonelle sensoriske ... -
Environmental sound classification on microcontrollers using Convolutional Neural Networks
Nordby, Jon Opedal (Master thesis, 2019)Noise is a growing problem in urban areas, and according to the WHO is the second environmental cause of health problems in Europe. Noise monitoring using Wireless Sensor Networks are being applied in order to understand ... -
Exploration of LET dependent effects in proton beam therapy using machine learning analysis of TL glow curves from CaSO4:Tm and LTB:Cu
Eriksen, Erling Ween (Master thesis, 2023)This thesis describes an investigation into the depth-dependent effects in proton radiation, evaluated by the use of Thermoluminescence Dosimetry (TLD) with CaSO4:Tm and LTB:Cu as target materials. Data collected on these ... -
Exploring the transition from traditional data analysis to machine- and deep learning approaches
Helin, Runar (PhD Thesis;2023:47, Doctoral thesis, 2023)Data analysis methods based on machine- and deep learning approaches are continuously replacing traditional methods. Models based on deep learning (DL) are applicable to many problems and often have better prediction ... -
Fault analysis of integrated circuit using fixed time events and clustering of time series data
Hvidsten, Jardar (Master thesis, 2020)The evolution of society is strongly dependent on technology development. Hardware (HW) development is crucial, however software (SW) development has become increasingly important in recent years due to the automation and ... -
Fish tracking using detection in aquaculture : a pilot study
Holmboe, Jens Kristian Røed (Master thesis, 2023)Use two different detection models and combine them with a tracking algorithm to be able to track fish that can be used in further fish welfare applications.