• 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, ...
    • 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. ...
    • 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), Book; Conference object; Peer reviewed, 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 ...
    • 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;, Chapter; Conference object; Peer reviewed, 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 ...
    • Kvasir-Capsule, a video capsule endoscopy dataset 

      Smedsrud, Pia H; Thambawita, Vajira L B; Hicks, Steven; Gjestang, Henrik; Olsen Nedrejord, Oda; Næss, Espen; Borgli, Hanna; Jha, Debesh; Berstad, Tor Jan; Eskeland, Sigrun Losada; Lux, Mathias; Espeland, Håvard; Petlund, Andreas; Dang Nguyen, Duc Tien; Garcia, Enrique; Johansen, Dag; Schmidt, Peter Thelin; Toth, Ervin; Hammer, Hugo Lewi; de Lange, Thomas; Riegler, Michael Alexander; Halvorsen, Pål (Scientific Data;8, Article number: 142 (2021), Peer reviewed; Journal article, 2021-05-27)
      Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work ...
    • LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification 

      Jha, Debesh; Yazidi, Anis; Riegler, Michael Alexander; Johansen, Dag; Johansen, Håvard D.; Halvorsen, Pål (Lecture Notes in Computer Science;Volume 12606, Chapter; Peer reviewed; Conference object; Journal article, 2021-02-21)
      Deep Neural Networks (DNNs) have become the de-facto standard in computer vision, as well as in many other pattern recognition tasks. A key drawback of DNNs is that the training phase can be very computationally expensive. ...
    • Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction 

      Hicks, Steven; Andersen, Jorunn Marie; Witczak, Oliwia; Lasantha Bandara Thambawita, Vajira; Halvorsen, Pål; Hammer, Hugo Lewi; Haugen, Trine B.; Riegler, Michael Alexander (Scientific Reports;9, Article number: 16770 (2019), Journal article; Peer reviewed, 2019-10-24)
      Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human reproduction, clinical and biological data are ...
    • Organiser Team at ImageCLEFlifelog 2020: A Baseline Approach for Moment Retrieval and Athlete Performance Prediction using Lifelog Data 

      Le, Tu-Khiem; Ninh, Van-Tu; Zhou, Liting; Nguyen-Ngoc, Minh-Huy; Piras, Luca; Riegler, Michael Alexander; Halvorsen, Pål; Lux, Mathias; Tran, Minh-Triet; Healy, Graham; Gurrin, Cathal; Dang Nguyen, Duc Tien (CEUR Workshop Proceedings;Volume 2696, Journal article; Peer reviewed, 2020)
      For the LMRT task at ImageCLEFlifelog 2020, LIFER 3.0, a new version of the LIFER system with improvements in the user in- terface and system affordance, is used and evaluated via feedback from a user experiment. In addition, ...
    • Overview of ImageCLEF Lifelog 2020: Lifelog Moment Retrieval and Sport Performance Lifelog 

      Ninh, Van-Tu; Le, Tu-Khiem; Zhou, Liting; Piras, Luca; Riegler, Michael Alexander; Halvorsen, Pål; Lux, Mathias; Tran, Minh-Triet; Gurrin, Cathal; Dang Nguyen, Duc Tien (CEUR Workshop Proceedings;Volume 2696, Journal article; Peer reviewed, 2020)
      This paper describes the fourth edition of Lifelog challenges in ImageCLEF 2020. In this edition, the Lifelog challenges consist of two tasks which are Lifelog Moments Retrieval (LMRT) and Sport Per- formance Lifelog (SPLL). ...
    • THREAT: A Large Annotated Corpus for Detection of Violent Threats 

      Hammer, Hugo Lewi; Riegler, Michael Alexander; Øvrelid, Lilja; Velldal, Erik (International Workshop on Content-Based Multimedia Indexing, CBMI;2019 International Conference on Content-Based Multimedia Indexing (CBMI), Conference object; Journal article, 2019-10-21)
      Understanding, detecting, moderating and in extreme cases deleting hateful comments in online discussions and social media are well-known challenges. In this paper we present a dataset consisting of a total of around 30000 ...