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Deep inspiration breath-hold in stereotactic and conventional fractionated radiotherapy of lesions in the lung
(Master thesis, 2021)The purpose of the clinical study was to evaluate lung cancer patients’ ability to perform deep inspiration breath-hold (DIBH) during CT simulation and throughout the treatment course of radiation therapy (RT). In addition, ... -
Deep inspiration breath-hold in stereotactic and conventional fractionated radiotherapy of lesions in the lung
(Master thesis, 2021-05)The purpose of the clinical study was to evaluate lung cancer patients’ ability to perform deep inspiration breath-hold (DIBH) during CT simulation and throughout the treatment course of radiation therapy (RT). In addition, ... -
Deep Learning - Deep Waters? A Study of Deep Learning in the Norwegian Middle School
(Master thesis, 2021)This thesis explores the term deep learning and its position in the Norwegian school. The term was introduced in the renewal of the curriculum in 2020 and is now a part of teachers’ classroom practice. The purpose of the ... -
A Deep Learning Approach To Dead-Reckoning Navigation For Autonomous Underwater Vehicles With Limited Sensor Payloads
(OCEANS;OCEANS 2021: San Diego – Porto, Conference object, 2022)This paper presents a deep learning approach to aid dead-reckoning (DR) navigation using a limited sensor suite. A Recurrent Neural Network (RNN) was developed to predict the relative horizontal velocities of an Autonomous ... -
A Deep Learning Approach to Dynamic Passive RTT
(2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC);, Conference object, 2019)The Round-Trip Time (RTT) is a property of the path between a sender and a receiver communicating with Transmission Control Protocol (TCP) over an IP network and over the public Internet. The end-to-end RTT value influences ... -
A Deep Learning Approach to Dynamic Passive RTT Prediction Model for TCP
(IEEE International Conference Performance, Computing and Communications (IPCCC);, Conference object, 2020-01-16)The Round-Trip Time (RTT) is a property of the path between a sender and a receiver communicating with Transmission Control Protocol (TCP) over an IP network and over the public Internet. The end-to-end RTT value influences ... -
Deep learning for automated polyp detection and localization in colonoscopy
(Master thesis, 2022)Gastrointestinal (GI) tract comprises organs from mouth to anus. Multiple diseases can occur in the GI tract. Among the different diseases in the digestive system, the most commonly found cancer in the gastrointestinal ... -
Deep Learning for Classifying Physical Activities from Accelerometer Data
(Sensors;Volume 21 / Issue 16, Peer reviewed; Journal article, 2021-08-18)Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening ... -
Deep learning for crop instance segmentation
(ACIT;2022, Master thesis, 2022)This thesis explores object detection with instance segmentation in relation to agriculture. For the purpose of discovering a detection model that could potentially boost robotic greenhouse harvesters with newer and ... -
Deep learning with cellular automaton-based reservoir computing
(Complex Systems;Volume 26, Issue 4, Journal article; Peer reviewed, 2017)Recurrent neural networks (RNNs) have been a prominent concept wiithin artificial intelligence. They are inspired by biological neural net works (BNNs) and provide an intuitive and abstract representation of how BNNs work. ... -
Deep Learning with EEG Data
(Master thesis, 2023)Electroencephalogram (EEG) data has shown great promise but requires sophisticated methods due to the complex spatial and temporal patterns found in such data, so this research was conducted with the objective to investigate ... -
A deep learning-based tool for automatic brain extraction from functional magnetic resonance images of rodents
(Peer reviewed; Journal article, 2021)Removing skull artifacts from functional magnetic images (fMRI) is a well understood and frequently encountered problem. Because the fMRI field has grown mostly due to human studies, many new tools were developed to handle ... -
Deep Politics: Community Adaptations to Political Clientelism in 21st Century Mexico
(Latin American research review;51(2), Journal article; Peer reviewed, 2016)The specific contribution of this study is to explore how a communitarian lifeworld prepares the ground for practices of political clientelism without requiring the “foundational favor” noted in other contexts. Based on ... -
«Deep reading» i biblioteket: et kritisk lys på håndteringen av e-bøker i fag- og folkebibliotek
(Nordisk Tidsskrift for informationsvitenskap- og kulturformidling;4(1), Journal article; Peer reviewed, 2015)Bibliotekene ivrer etter å kunne tilby e-bøker til lånerne. I Norge har de fleste fagbibliotekene lenge hatt store samlinger av e-bøker, mens folkebibliotekene først fra 2013 kunne tilby norskspråklige titler. I denne ... -
Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources
(Sensors;Volume 22 / Issue 7, Peer reviewed; Journal article, 2022-04-06)Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them ... -
Deep, surface, or both? A study of occupational therapy students’ learning concepts
(Occupational Therapy International;Volume 2018, Journal article; Peer reviewed, 2018-08-07)Background: Students’ conceptualization of learning has been associated with their approaches to studying. However, whether students’ learning concepts are associated with their personal characteristics is unknown. Aim: ... -
DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine
(Scientific Reports;11, Article number: 21896 (2021), Peer reviewed; Journal article, 2021-11-09)Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic ... -
DeepNAVI: A deep learning based smartphone navigation assistant for people with visual impairments
(Expert Systems With Applications;, Peer reviewed; Journal article, 2022)Navigation assistance is an active research area, where one aim is to foster independent living for people with vision impairments. Despite the fact that many navigation assistants use advanced technologies and methods, ... -
DeepSynthBody: the beginning of the end for data deficiency in medicine
(OsloMet Avhandling 2021;Nr. 45, Doctoral thesis; Peer reviewed, 2021)Recent advancements in technology have made arti ficial intelligence (AI) a popular tool in the medical domain, especially machine learning (ML) methods, which is a subset of AI. In this context, a goal is to research and ... -
Defining the limitations and opportunities in the consultation with the Sámi: The cases of the Arctic Railway and the Davvi Vindpark
(The Arctic Yearbook;2021 -Defining and Mapping the Arctic, Peer reviewed; Journal article, 2021)The results of this study point to a number of limitations in the consultation with the Sámi, such as incomplete information, lack of transparency and the failure of governments to build relationships based on trust with ...