Blar i Brage NMBU på forfatter "Liland, Kristian Hovde"
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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 ... -
Confidence ellipsoids for ASCA models based on multivariate regression theory
Liland, Kristian Hovde; Smilde, Age K.; Marini, Federico; Næs, Tormod (Journal article; Peer reviewed, 2018) -
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, ... -
Deciphering transcriptional regulation using deep neural networks
Førrisdal, Julie Wollebæk (Master thesis, 2023)The DNA holds the recipe of all life functions. To decipher the instructions, one has to learn and understand its complex syntax. The non-coding DNA contains regulatory elements, that are essential to control and activate ... -
Deep convolutional neural network recovers pure absorbance spectra from highly scatter‐distorted spectra of cells
Magnussen, Eirik Almklov; Solheim, Johanne Heitmann; Blazhko, Uladzislau; Tafintseva, Valeria; Tøndel, Kristin; Liland, Kristian Hovde; Dzurendova, Simona; Shapaval, Volha; Sandt, Christophe; Borondics, Ferenc; Kohler, Achim (Peer reviewed; Journal article, 2020) -
Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra
Magnussen, Eirik Almklov; Zimmermann, Boris; Blazhko, Uladzislau; Dzurendová, Simona; Dupuy--Galet, Benjamin Xavier; Byrtusova, Dana; Muthreich, Florian; Tafintseva, Valeria; Liland, Kristian Hovde; Tøndel, Kristin; Shapaval, Volha; Kohler, Achim (Peer reviewed; Journal article, 2022)Infrared spectroscopy delivers abundant information about the chemical composition, as well as the structural and optical properties of intact samples in a non-destructive manner. We present a deep convolutional neural ... -
Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra
Magnussen, Eirik Almklov; Zimmermann, Boris; Blazhko, Uladzislau; Dzurendová, Simona; Dupuy--Galet, Benjamin Xavier; Byrtusova, Dana; Muthreich, Florian; Tafintseva, Valeria; Liland, Kristian Hovde; Tøndel, Kristin; Shapaval, Volha; Kohler, Achim (Peer reviewed; Journal article, 2022) -
DeepGene : gene finding based on upstream sequence data
Almestrand, Trude Haug (Master thesis, 2022)Genome annotation is a process of identifying functional elements along a genome. By correctly locating and finding the information stored within a sequence, knowledge about structural features and functional roles can be ... -
Designing a risk-based surveillance program for Mycobacterium avium ssp. paratuberculosis in Norwegian dairy herds using multivariate statistical process control analysis
Whist, Anne C; Liland, Kristian Hovde; Jonsson, Malin E; Sæbø, Solve; Sviland, Ståle; Østerås, Olav; Norström, Madelaine; Hopp, Petter (Journal article; Peer reviewed, 2014)Surveillance programs for animal diseases are critical to early disease detection and risk estimation and to documenting a population’s disease status at a given time. The aim of this study was to describe a risk-based ... -
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 ... -
Distribution based truncation for variable selection in subspace methods for multivariate regression
Liland, Kristian Hovde; Høy, Martin; Martens, Harald; Sæbø, Solve (Journal article; Peer reviewed, 2013)Analysis of data containing a vast number of features, but only a limited number of informative ones, requires methods that can separate true signal from noise variables. One class of methods attempting this is the sparse ... -
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 ... -
Effect of Liquid Absorbent Pads and Packaging Parameters on Drip Loss and Quality of Chicken Breast Fillets
Pettersen, Marit Kvalvåg; Nilsen-Nygaard, Julie; Hansen, Anlaug Ådland; Carlehög, Mats; Liland, Kristian Hovde (Peer reviewed; Journal article, 2021)Visible liquid inside food packages is perceived as unattractive to consumers, and may result in food waste—a significant factor that can compromise sustainability in food value chains. However, an absorber with overdimensioned ... -
Effects of glucose availability in Lactobacillus sakei; metabolic change and regulation of the proteome and transcriptome
McLeod, Anette; Mosleth, Ellen Færgestad; Rud, Ida; Branco dos Santos, Filipe; Snipen, Lars-Gustav; Liland, Kristian Hovde; Axelsson, Lars (Journal article; Peer reviewed, 2017)Effects of glucose availability were investigated in Lactobacillus sakei strains 23K and LS25 cultivated in anaerobic, glucose-limited chemostats set at high (D = 0.357 h-1) and low (D = 0.045 h-1) dilution rates. We ... -
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 ... -
Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis
Kuchta, Miroslav; Wubshet, Sileshi Gizachew; Afseth, Nils Kristian; Mardal, Kent-Andre; Liland, Kristian Hovde (Peer reviewed; Journal article, 2022)In the process of converting food-processing by-products to value-addedingredients, fine grained control of the rawmaterials, enzymes and process conditionsensures the best possible yield and eco-nomic return. However, ... -
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 ... -
Evaluation of machine learning methods to decode transcriptional regulation
Jeyakumar, Harini (Master thesis, 2023)With large biological measurements made possible by the development of high-throughput technology, it allows for the study of genomic data. In transcriptional regulation the cell controls the translation of DNA to RNA, and ... -
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 ...