Blar i TKD - Institutt for informasjonsteknologi på forfatter "Halvorsen, Pål"

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    • Affect Recognition in Muscular Response Signals 

      Boeker, Matthias; Jakobsen, Petter; Riegler, Michael; Stabell, Lena Antonsen; Fasmer, Ole Bernt; Halvorsen, Pål; Hammer, Hugo Lewi (Peer reviewed; Journal article, 2023)
      This study investigated the potential of recognising arousal in motor activity collected by wrist- worn accelerometers. We hypothesise that emotional arousal emerges from the generalised central nervous system which ...

    • Artificial intelligence in dry eye disease 

      Storås, Andrea Marheim; Strumke, Inga; Riegler, Michael Alexander; Grauslund, Jakob; Hammer, Hugo Lewi; Yazidi, Anis; Halvorsen, Pål; Gundersen, Kjell Gunnar; Utheim, Tor Paaske; Jackson, Catherine Joan (The ocular surface;Volume 23, January 2022, Peer reviewed; Journal article, 2021-12-01)
      Dry eye disease (DED) has a prevalence of between 5 and 50%, depending on the diagnostic criteria used and population under study. However, it remains one of the most underdiagnosed and undertreated conditions in ophthalmology. ...

    • Artificial intelligence in the fertility clinic: status, pitfalls and possibilities 

      Riegler, Michael Alexander; Stensen, Mette Haug; Witczak, Oliwia; Andersen, Jorunn Marie; Hicks, Steven; Hammer, Hugo Lewi; Delbarre, Erwan; Halvorsen, Pål; Yazidi, Anis; Holst, Nicolai; Haugen, Trine B. (Human Reproduction;Volume 36, Issue 9, Peer reviewed; Journal article, 2021-07-29)
      In recent years, the amount of data produced in the field of assisted reproduction technology [ART] has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, ...

    • Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge 

      Ali, Sharib; Ghatwary, Noha; Jha, Debesh; Isik-Polat, Ece; Polat, Gorkem; Yang, Cheng; Li, Wuyang; Galdran, Adrian; Ballester, Miguel Angel Gonzalez; Thambawita, Vajira L B; Hicks, Steven; Poudel, Sahadev; Lee, Sang-Woong; Jin, Ziyi; Gan, Tianyuan; Yu, Chenghui; Yan, JiangPeng; Yeo, Doyeob; Lee, Hyunseok Lee; Tomar, Nikhil Kumar; Haitham, Mahmood; Ahmed, Amr; Riegler, Michael Alexander; Daul, Christian; Halvorsen, Pål; Rittscher, Jens; Salem, Osama E.; Lamarque, Dominique; Cannizzaro, Renato; Realdon, Stefano; de Lange, Thomas; East, James E (Peer reviewed; Journal article, 2024)
      Polyps are well‑known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal ...

    • Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure 

      Storås, Andrea; Riegler, Michael Alexander; Haugen, Trine B.; Thambawita, Vajira L B; Hicks, Steven Alexander; Hammer, Hugo Lewi; Kakulavarapu, Radhika; Halvorsen, Pål; Stensen, Mette Haug (Chapter; Conference object, 2023)
      The in vitro fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine and ...

    • CELLULAR, A Cell Autophagy Imaging Dataset 

      al Outa, Amani; Hicks, Steven; Thambawita, Vajira L B; Andresen, Siri; Enserink, Jorrit Martijn; Halvorsen, Pål; Riegler, Michael Alexander; Knævelsrud, Helene (Peer reviewed; Journal article, 2023)
      Cells in living organisms are dynamic compartments that continuously respond to changes in their environment to maintain physiological homeostasis. While basal autophagy exists in cells to aid in the regular turnover of ...

    • A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging 

      Jha, Debesh; Ali, Sharib; Hicks, Steven; Thambawita, Vajira L B; Borgli, Hanna; Smedsrud, Pia H.; de Lange, Thomas; Pogorelov, Konstantin; Wang, Xiaowei; Harzig, Philipp; Tran, Minh-Triet; Meng, Wenhua; Hoang, Trung-Hieu; Dias, Danielle; Ko, Tobey H.; Agrawal, Taruna; Ostroukhova, Olga; Khan, Zeshan; Tahir, Muhammed Atif; Liu, Yang; Chang, Yuan; Kirkerød, Mathias; Johansen, Dag; Lux, Mathias; Johansen, Håvard D.; Riegler, Michael; Halvorsen, Pål (Peer reviewed; Journal article, 2021)
      Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large number of highly lethal GI cancers. Early GI cancer precursors are often missed during the endoscopic surveillance. The high missed ...

    • A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation 

      Jha, Debesh; Smedsrud, Pia; Johansen, Dag; de Lange, Thomas; Johansen, Håvard D.; Halvorsen, Pål; Riegler, Michael Alexander (IEEE journal of biomedical and health informatics; Volume: 25, Issue: 6, June 2021, Journal article; Peer reviewed, 2021-01-05)
      Colonoscopy is considered the gold standard for detection of colorectal cancer and its precursors. Existing examination methods are, however, hampered by high overall miss-rate, and many abnormalities are left undetected. ...

    • DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine 

      Thambawita, Vajira; Isaksen, Jonas L.; Hicks, Steven A.; Ghouse, Jonas; Ahlberg, Gustav; Linneberg, Allan; Grarup, Niels; Ellervik, Christina; Olesen, Morten Salling; Hansen, Torben; Graff, Claus; Holstein-Rathlou, Niels-Henrik; Strümke, Inga; Hammer, Hugo L.; Maleckar, Mary M.; Halvorsen, Pål; Riegler, Michael A.; Kanters, Jørgen K. (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 ...

    • Diagnosing Schizophrenia from Activity Records using Hidden Markov Model Parameters 

      Boeker, Matthias; Riegler, Michael; Hammer, Hugo Lewi; Halvorsen, Pål; Fasmer, Ole Bernt; Jakobsen, Petter (Annual IEEE Symposium on Computer-Based Medical Systems;2021 IEEE 34th International Symposium on Computer-Based Medical Systems, Conference object, 2021-07-12)
      The diagnosis of Schizophrenia is mainly based on qualitative characteristics. With the usage of portable devices which measure activity of humans, the diagnosis of Schizophrenia can be enriched through quantitative features. ...

    • DivergentNets: Medical Image Segmentation by Network Ensemble 

      Thambawita, Vajira L B; Hicks, Steven; Halvorsen, Pål; Riegler, Michael (CEUR Workshop Proceedings;Vol-2886 - Proceedings of the 3rd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2021), Conference object, 2021)
      Detection of colon polyps has become a trending topic in the intersecting fields of machine learning and gastrointestinal endoscopy. The focus has mainly been on per-frame classification. More recently, polyp segmentation ...

    • DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation 

      Jha, Debesh; Riegler, Michael Alexander; Johansen, Dag; Halvorsen, Pål; Johansen, Håvard D. (IEEE International Symposium on Computer-Based Medical Systems; 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), Conference object, 2020-09-01)
      Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image ...

    • Efficient live and on-demand tiled HEVC 360 VR video streaming 

      Jeppsson, Mattis; Espeland, Håvard; Kupka, Tomas; Langseth, Ragnar; Petlund, Andreas; Peng, Qiaoqiao; Xue, Chuansong; Johansen, Dag; Pogorelov, Konstantin; Stensland, Håkon Kvale; Griwodz, Carsten; Riegler, Michael; Halvorsen, Pål (International Journal of Semantic Computing;Vol. 13, No. 03, Journal article; Peer reviewed, 2019-10-24)
      360∘ panorama video displayed through Virtual Reality (VR) glasses or large screens offers immersive user experiences, but as such technology becomes commonplace, the need for efficient streaming methods of such high-bitrate ...

    • Enhancing investigative interview training using a child avatar system: a comparative study of interactive environments 

      Zohaib Hassan, Syed; Shafiee Sabet, Saeed; Riegler, Michael Alexander; Baugerud, Gunn Astrid; Ko, Hayley Manalang; Salehi, Pegah; Røed, Ragnhild Klingenberg; Sinkerud Johnson, Miriam; Halvorsen, Pål (Peer reviewed; Journal article, 2023)
      The impact of investigative interviews by police and Child Protective Services (CPS) on abused children can be profound, making effective training vital. Quality in these interviews often falls short and current training ...

    • Enhancing questioning skills through child avatar chatbot training with feedback 

      Røed, Ragnhild Klingenberg; Baugerud, Gunn Astrid; Zohaib Hassan, Syed; Shafiee Sabet, Saeed; Salehi, Pegah; Powell, Martine B.; Riegler, Michael Alexander; Halvorsen, Pål; Sinkerud Johnson, Miriam (Peer reviewed; Journal article, 2023)
      Training child investigative interviewing skills is a specialized task. Those being trained need opportunities to practice their skills in realistic settings and receive immediate feedback. A key step in ensuring the ...

    • Explaining deep neural networks for knowledge discovery in electrocardiogram analysis 

      Hicks, Steven; Isaksen, Jonas L; Thambawita, Vajira L B; Ghouse, Jonas; Ahlberg, Gustav; Linneberg, Allan; Grarup, Niels; Strumke, Inga; Ellervik, Christina; Olesen, Morten Salling; Hansen, Torben; Graff, Claus; Holstein-Rathlou, Niels-Henrik; Halvorsen, Pål; Maleckar, Mary Margot Catherine; Riegler, Michael; Kanters, Jørgen K (Scientific Reports;11, Article number: 10949 (2021), Peer reviewed; Journal article, 2021-05-26)
      Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any ...

    • File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments 

      Ovesen, Aril Bernhard; Nordmo, Tor-Arne Schmidt; Johansen, Håvard D.; Riegler, Michael Alexander; Halvorsen, Pål; Johansen, Dag (Information;Volume 12, Issue 10, Peer reviewed; Journal article, 2021-10-18)
      In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform ...

    • Flexible device compositions and dynamic resource sharing in PCIe interconnected clusters using Device Lending 

      Markussen, Jonas Sæther; Bjørlykke Kristiansen, Lars; Borgli, Rune Johan; Stensland, Håkon Kvale; Seifert, Friedrich; Riegler, Michael Alexander; Griwodz, Carsten; Halvorsen, Pål (Cluster Computing volume;Volume 23, issue 2, Journal article; Peer reviewed, 2019-09-21)
      Modern workloads often exceed the processing and I/O capabilities provided by resource virtualization, requiring direct access to the physical hardware in order to reduce latency and computing overhead. For computers ...

    • GANEx: A complete pipeline of training, inference and benchmarking GAN experiments 

      Thambawita, Vajira; Hammer, Hugo Lewi; Riegler, Michael Alexander; Halvorsen, Pål (International Workshop on Content-Based Multimedia Indexing, CBMI;, Conference object, 2019-10-21)
      Deep learning (DL) is one of the standard methods in the field of multimedia research to perform data classification, detection, segmentation and generation. Within DL, generative adversarial networks (GANs) represents a ...

    • GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos 

      Monakhov, Vladimir; Thambawita, Vajira L B; Halvorsen, Pål; Riegler, Michael (Peer reviewed; Journal article, 2023)
      The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep ...