Browsing Faculty of Science and Technology (RealTek) by Author "Liland, Kristian Hovde"
Now showing items 1-20 of 41
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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 ... -
Anomaly detection in industrial time series sensor data
Cherednikov, Ivan (Master thesis, 2023)Anomaly detection in industrial time series data is essential for identifying and preventing potential issues in production processes, ensuring high product quality and reducing downtime. This master's thesis investigates ... -
Beyond extractive : advancing abstractive automatic text summarization in Norwegian with transformers
Navjord, Jørgen Johnsen; Korsvik, Jon-Mikkel Ryen (Master thesis, 2023)Automatic summarization is a key area in natural language processing (NLP) and machine learning which attempts to generate informative summaries of articles and documents. Despite its evolution since the 1950s, research ... -
Can Tabular Generative Models generate realistic synthetic Near Infrared spectroscopic data?
Finnøy, Isak (Master thesis, 2023)In this thesis, we evaluated the performance of two generative models, Conditional Tabular Generative Adversarial Network (CTGAN) and Tabular Variational Autoencoder (TVAE), from the open-source library Synthetic Data Vault ... -
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 fish monitoring : challenges and possibilities
Breiteig, Mikal (Master thesis, 2023)This master's thesis focuses on the evaluation and exploration of detection and tracking algorithms for fish in a dense underwater environment. The primary objectives were to achieve precise and accurate fish detection and ... -
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, ... -
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 ... -
Drivers behind variation in welfare, quality, and production performance in Atlantic salmon farming production data
Alvestad, René (PhD Thesis;2021:46, Doctoral thesis, 2021)Atlantic salmon aquaculture is an important industry in Norway and farmed salmon is among the most economically important global aquaculture species. Despite this, the growth of the industry has stagnated in Norway and it ... -
Efficient model selection in the Tikhonov Regularization framework and pre-processing of spectroscopic data
Skogholt, Joakim (PhD Thesis;2019:99, Doctoral thesis, 2019)Machine learning is a hot topic in today's society. Data sets of varying sizes show up in a number of contexts, and learning from data sets is important for answering many questions. There is a plethora of methods that can ... -
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 ... -
Evaluation of machine learning approaches for prediction of protein coding genes in prokaryotic DNA sequences
Sandvik, Yva Jacob (Master thesis, 2022)According to the National Human Genome Research Institute the amount of genomic data generated on a yearly basis is constantly increasing. This rapid growth in genomic data has led to a subsequent surge in the demand for ... -
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 ... -
Explore the effect of data augmentation of spectroscopic data for deep learning models
Naveed, Talha (Master thesis, 2022)This study aimed to explore the effect of data augmentation techniques to improve the performance of deep learning models on data sets that contain more features than samples. The data set used as an example for this case ... -
Exploring the possibilities of obtaining CNN-quality classification models without using convolutional neural networks
Arfan, Amir Inaamullah (Master thesis, 2022)In this thesis, we pursue the success of Convolutional Neural Networks for image classification tasks. We explore the possibilities of achieving state-of-the-art performance without explicitly using CNNs on 2D grayscale ... -
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 ... -
Fully convolutional neural network for semantic segmentation on CT scans of pigs
Pollestad, Jarand Hornseth (Master thesis, 2019)Identifying the shape and location of structures within medical images is useful for purposes such as diagnosis and research. This is a cumbersome task if done manually. Recent advances in computer vision and in particular ... -
Hyperspectral imaging : algorithmic advances in variable selection and applications to wood science
Stefansson, Petter (PhD Thesis;2019:77, Doctoral thesis, 2019)According to Beer’s Law there is a linear dependence between the absorbance of a material and the concentration of an absorbing species in the material. Thus, if one is interested in modeling the concentration of an absorbing ...