Blar i Brage NMBU på forfatter "Liland, Kristian Hovde"
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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 ... -
fixedTimeEvents: An R package for the distribution of distances between discrete events in fixed time
Liland, Kristian Hovde; Snipen, Lars-Gustav (Peer reviewed; Journal article, 2016)When a series of Bernoulli trials occur within a fixed time frame or limited space, it is often interesting to assess if the successful outcomes have occurred completely at random, or if they tend to group together. One ... -
FTIR-based hierarchical modeling for prediction of average molecular weights of protein hydrolysates
Kristoffersen, Kenneth Aase; Liland, Kristian Hovde; Böcker, Ulrike; Wubshet, Sileshi Gizachhew; Lindberg, Diana; Horn, Svein Jarle; Afseth, Nils Kristian (Journal article; Peer reviewed, 2019)In the presented study, Fourier-transform infrared (FTIR) spectroscopy is used to predict the average molecular weight of protein hydrolysates produced from protein-rich by-products from food industry using commercial ... -
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 ... -
Gene expression response in peripheral blood cells of petroleum workers exposed to sub-ppm benzene levels
Jørgensen, Katarina Mariann; Mosleth, Ellen Færgestad; Liland, Kristian Hovde; Hopf, Nancy Brenna; Holdhus, Rita; Stavrum, Anne-Kristin; Gjertsen, Bjørn Tore; Kirkeleit, Jorunn (Journal article; Peer reviewed, 2018) -
Gene Expression Response in Peripheral Blood Cells of Petroleum Workers Exposed to Sub-Ppm Benzene Levels
Jørgensen, Katarina Mariann; Mosleth, Ellen Færgestad; Liland, Kristian Hovde; Hopf, Nancy Brenna; Holdhus, Rita; Stavrum, Anne-Kristin; Gjertsen, Bjørn Tore; Kirkeleit, Jorunn (Peer reviewed; Journal article, 2018) -
Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics
Huynh, Bao Ngoc; Grøndahl, Aurora Rosvoll; Tomic, Oliver; Liland, Kristian Hovde; Knudtsen, Ingerid Søberg Skjei; Hoebers, Frank; van Elmpt, Wouter; Malinen, Eirik; Dale, Einar; Futsæther, Cecilia Marie (Peer reviewed; Journal article, 2023) -
hoggorm: a python library for explorative multivariate statistics
Tomic, Oliver; Graff, Thomas; Liland, Kristian Hovde; Næs, Tormod (Peer reviewed; Journal article, 2019) -
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 ... -
Iterative re-weighted covariates selection for robust feature selection modelling in the presence of outliers (irCovSel)
Mishra, Puneet; Liland, Kristian Hovde (Peer reviewed; Journal article, 2022) -
Iterative re-weighted multilinear partial least squares modelling for robust predictive modelling
Mishra, Puneet; Liland, Kristian Hovde (Journal article; Peer reviewed, 2023) -
Medical image representations in cancer segmentation
Granheim, Markus Ola Holte (Master thesis, 2021)Purpose Cancer is the second leading cause of death globally and was responsible for an estimated 9.6 million deaths in 2018 [1]. One of the treatments used to cure cancer is radiotherapy, where a precise delineation of ... -
microclass: An R-package for 16S taxonomy classification
Liland, Kristian Hovde; Vinje, Hilde; Snipen, Lars-Gustav (Journal article; Peer reviewed, 2017)Background Taxonomic classification based on the 16S rRNA gene sequence is important for the profiling of microbial communities. In addition to giving the best possible accuracy, it is also important to quantify uncertainties ... -
micropan: An R-package for microbial pan-genomics
Snipen, Lars-Gustav; Liland, Kristian Hovde (Journal article; Peer reviewed, 2015) -
Mining medical academic articles using recurrent neural networks
Radwan, Mohamed (Master thesis, 2021)In this thesis, we present our methods and results for mining the MedMentions data [Mohan and Li, 2019]. We propose a pipeline for combining mention classification and mention disambiguation. We will use the Long Short ... -
Mining online community data: The nature of ideas in online communities
Christensen, Kasper Knoblauch; Liland, Kristian Hovde; Kvaal, Knut; Risvik, Einar; Biancolillo, Alessandra; Scholderer, Joachim; Nørskov, Sladjana; Næs, Tormod (Journal article; Peer reviewed, 2017)Ideas are essential for innovation and for the continuous renewal of a firm’s product offerings. Previous research has argued that online communities contain such ideas. Therefore, online communities such as forums, Facebook ... -
Model-based pre-processing in Raman spectroscopy of biological samples
Liland, Kristian Hovde; Kohler, Achim; Afseth, Nils Kristian (Journal article; Peer reviewed, 2016)Model-based pre-processing has become wide spread in spectroscopy and is the standard procedure in Fourier-transform infrared spectroscopy. It has also been shown to give valuable contributions in Raman spectroscopy. ...