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Compact representation for memory-efficient storage of images using genetic algorithm-guided key pixel selection
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-11-04)In the past few years, we have observed rapid growth in digital content. Even in the biological domain, the arrival of microscopic and nanoscopic images and videos captured for biological investigations increases the need for space to store them. Hence, storing these data in a storage-efficient manner is a pressing need. In this work, we have introduced a compact image representation technique with ... -
AI-Based Cropping of Ice Hockey Videos for Different Social Media Representations
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-23)Sports multimedia is among the most prominent types of content distributed across social media today, and the retargeting of videos for diverse aspect ratios is essential for a suitable representation on different social media platforms. In this respect, ice hockey is quite challenging due to its agile movement pattern and speed, and because the main reference point (puck) is very small. In this ... -
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
(Journal article; Tidsskriftartikkel; Peer reviewed, 2025-09-05)Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is ... -
A Theoretical and Empirical Analysis of 2D and 3D Virtual Environments in Training for Child Interview Skills
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-12)This paper presents a detailed study of an AI-driven platform designed for the training of child welfare and law enforcement professionals in conducting investigative interviews with maltreated children. It achieves a subjective simulation of interview situation through the integration of fine-tuned GPT-3 models within the Unity framework. The study recruited participants from a range of backgrounds, ... -
Machine learning based prognostics and statistical optimization of the performance of biogas-biodiesel blends powered engine
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-09-12)In this study, waste biomass-derived biogas was employed as the main fuel while the biodiesel-diesel blend was used as pilot fuel. This paper describes the development of a Decision Tree and Response Surface methodology-based statistical framework for prediction modeling and optimization. The compression ratio, fuel injection time, fuel injection pressure, and biogas flow rate were employed as ... -
Leveraging explainable artificial intelligence for early prediction of bloodstream infections using historical electronic health records
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-11-14)Bloodstream infections (BSIs) are a severe public health threat due to their rapid progression into critical conditions like sepsis. This study presents a novel eXplainable Artificial Intelligence (XAI) framework to predict BSIs using historical electronic health records (EHRs). Leveraging a dataset from St. Olavs Hospital in Trondheim, Norway, encompassing 35,591 patients, the framework integrates ... -
Enhancing Medical Image Quality Using Fractional Order Denoising Integrated with Transfer Learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-29)In medical imaging, noise can significantly obscure critical details, complicating diagnosis and treatment. Traditional denoising techniques often struggle to maintain a balance between noise reduction and detail preservation. To address this challenge, we propose an “Efficient Transfer-Learning-Based Fractional Order Image Denoising Approach in Medical Image Analysis (ETLFOD)” method. Our approach ... -
AI-Based Cropping of Ice Hockey Videos for Different Social Media Representations
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-23)Sports multimedia is among the most prominent types of content distributed across social media today, and the retargeting of videos for diverse aspect ratios is essential for a suitable representation on different social media platforms. In this respect, ice hockey is quite challenging due to its agile movement pattern and speed, and because the main reference point (puck) is very small. In this ... -
Variation in Accelerometer-Derived Instantaneous Acceleration Distribution Curves of Elite Male Soccer Players According to Playing Position: A Pilot Study
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-09-23)The incorporation of triaxial accelerometers into Global Positioning Systems (GPS) has significantly advanced our understanding of accelerations in sports. However, inter-positional differences are unknown. This study aimed to explore the variability of acceleration and deceleration (Acc) distribution curves according to players’ positions during soccer matches. Thirty-seven male players from a ... -
Using power system modelling outputs to identify weather-induced extreme events in highly renewable systems
(Journal article; Tidsskriftartikkel, 2024-04-26)In highly renewable power systems the increased weather dependence can result in new resilience challenges, such as renewable energy droughts, or a lack of sufficient renewable generation at times of high demand. The weather conditions responsible for these challenges have been well-studied in the literature. However, in reality multi-day resilience challenges are triggered by complex interactions ... -
A Theoretical and Empirical Analysis of 2D and 3D Virtual Environments in Training for Child Interview Skills
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-12)This paper presents a detailed study of an AI-driven platform designed for the training of child welfare and law enforcement professionals in conducting investigative interviews with maltreated children. It achieves a subjective simulation of interview situation through the integration of fine-tuned GPT-3 models within the Unity framework. The study recruited participants from a range of backgrounds, ... -
Propagating Transparency: A Deep Dive into the Interpretability of Neural Networks
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-19)In the rapidly evolving landscape of deep learning (DL), understanding the inner workings of neural networks remains a significant challenge. The need for transparency and accountability in DL models grows in importance as they become more prevalent in decision-making processes. Interpreting these models is key to addressing this challenge. This paper offers a comprehensive overview of interpretable ... -
Breast Cancer Detection and Analytics Using Hybrid CNN and Extreme Learning Machine
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-07-26)Early detection of breast cancer is essential for increasing survival rates, as it is one of the primary causes of death for women globally. Mammograms are extensively used by physicians for diagnosis, but selecting appropriate algorithms for image enhancement, segmentation, feature extraction, and classification remains a significant research challenge. This paper presents a computer-aided diagnosis ... -
In-network monitoring strategies for HPC cloud
(Conference object; Konferansebidrag, 2024)The optimized network architectures and interconnect technologies employed in high-performance cloud computing environments introduce challenges when it comes to developing monitoring solutions that effectively capture relevant network metrics. Moreover, network monitoring often involves capturing and analyzing a large volume of network traffic data. This process can introduce additional overhead ... -
In-hospital Mortality, Readmission, and Prolonged Length of Stay Risk Prediction Leveraging Historical Electronic Patient Records
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-09-14)Objective - This study aimed to investigate the predictive capabilities of historical patient records to predict patient adverse outcomes such as mortality, readmission, and prolonged length of stay (PLOS).<p> <p>Methods - Leveraging a de-identified dataset from a tertiary care university hospital, we developed an eXplainable Artificial Intelligence (XAI) framework combining tree-based and ... -
Inquiry-Based Linear Algebra Teaching and Learning in a Flipped Classroom Framework: A Case Study
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-07-17)Flipped Classroom (FC) approaches, which utilize video distribution via modern internet platforms, have recently gained interest as a pedagogical framework. Inquiry Based Mathematics Education (IBME) has proven to be a valid form of task design to motivate active learning and enhance classroom interactivity. This article presents a practical combination of introductory videos and inquiry-based class ... -
A review of information sources and analysis methods for data driven decision aids in child and adolescent mental health services
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-05-13)Objective: Clinical data analysis relies on effective methods and appropriate data. Recognizing distinctive clinical services and service functions may lead to improved decision-making. Our first objective is to categorize analytical methods, data sources, and algorithms used in current research on information analysis and decision support in child and adolescent mental health services (CAMHS). ... -
pNNCLR: Stochastic pseudo neighborhoods for contrastive learning based unsupervised representation learning problems
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-05-11)Nearest neighbor (NN) sampling provides more semantic variations than predefined transformations for selfsupervised learning (SSL) based image recognition problems. However, its performance is restricted by the quality of the support set, which holds positive samples for the contrastive loss. In this work, we show that the quality of the support set plays a crucial role in any nearest neighbor based ... -
Data note for gender perspectives on a flipped classroom environment
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-20)The present paper is a data note related to the paper “Gender perspectives on a flipped classroom environment”. The paper drew on an in-depth analysis of the interview with a single female student called Sofia and attempted to analyze different gender related interactions between students in group work situations experienced by this student. The transcript from this interview was translated from ... -
Using One App Only – Collecting a Comprehensive Set of Health-Related Data for Prevention of Chronic Conditions
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024)This paper presents the design, implementation and early tests of an app that collects a comprehensive set of health-related data, as part of the EU-project WARIFA. To achieve the main aim of the project – using AI to prevent chronic conditions – a wide range of data needs to be collected and stored at a backend server for processing. The methods and elements for creating this system are presented, ...
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