• 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 ...
    • 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 ...
    • 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, Conference object, 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. ...
    • MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation 

      Srivastava, Abhishek; Jha, Debesh; Chanda, Sukalpa; Pal, Umapada; Johansen, Håvard D.; Johansen, Dag; Riegler, Michael; Ali, Sharib; Halvorsen, Pål (IEEE journal of biomedical and health informatics;Volume: 26, Issue: 5, Peer reviewed; Journal article, 2021-12-23)
      Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of variable sizes and train on small and ...
    • Njord: a fishing trawler dataset 

      Nordmo, Tor-Arne Schmidt; Ovesen, Aril Bernhard; Juliussen, Bjørn Aslak; Hicks, Steven; Thambawita, Vajira L B; Johansen, Håvard D.; Halvorsen, Pål; Riegler, Michael Alexander; Johansen, Dag (Chapter, 2022)
      Fish is one of the main sources of food worldwide. The commercial fishing industry has a lot of different aspects to consider, ranging from sustainability to reporting. The complexity of the domain also attracts a lot of ...
    • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning 

      Jha, Debesh; Ali, Sharib; Tomar, Nikhil Kumar; Johansen, Håvard D.; Johansen, Dag; Rittscher, Jens; Riegler, Michael A.; Halvorsen, Pal (IEEE Access;Volume: 9, Peer reviewed; Journal article, 2021-03-04)
      Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of ...
    • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning 

      Jha, Debesh; Ali, Sharib; Tomar, Nikhil Kumar; Johansen, Håvard D.; Johansen, Dag; Rittscher, Jens; Riegler, Michael; Halvorsen, Pål (IEEE Access;Volume: 9, 2021, Peer reviewed; Journal article, 2021-03-04)
      Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of ...
    • ScopeSense: An 8.5-Month Sport, Nutrition, and Lifestyle Lifelogging Dataset 

      Riegler, Michael Alexander; Thambawita, Vajira; Nguyen, Thu; Hicks, Steven Alexander; Pettersen, Svein Arne; Telle-Hansen, Vibeke; Johansen, Dag; Jain, Ramesh; Halvorsen, Pål (Lecture Notes in Computer Science (LNCS);, Peer reviewed; Journal article, 2023)
      Nowadays, most people have a smartphone that can track their everyday activities. Furthermore, a significant number of people wear advanced smartwatches to track several vital biomarkers in addition to activity data. ...
    • Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events 

      Rongved, Olav Andre Nergård; Hicks, Steven; Thambawita, Vajira L B; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål (International Journal of Semantic Computing (IJSC);Volume 15, Issue 02, Peer reviewed; Journal article, 2021)
      Developing systems for the automatic detection of events in video is a task which has gained attention in many areas including sports. However, there are still a number of shortcomings with current systems, such as high ...