Blar i ODA Open Digital Archive på forfatter "Halvorsen, Pål"

Viser treff 41-60 av 76

    • Man vs. AI: An in silico study of polyp detection performance 

      Smedsrud, Pia Helen; Espeland, Håvard; Berstad, Tor Jan; Petlund, Andreas; de Lange, Thomas; Riegler, Michael; Halvorsen, Pål (Annual IEEE Symposium on Computer-Based Medical Systems;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      AI-based colon polyp detection systems have received much attention, and several products and prototypes report good results. In silico verification is a crucial step when developing such systems, but very few compare human ...

    • Mask-conditioned latent diffusion for generating gastrointestinal polyp images 

      Macháček, Roman; Mozaffari, Leila; Sepasdar, Zahra; Parasa, Sravanthi; Halvorsen, Pål; Riegler, Michael; Thambawita, Vajira L B; Machacek, Roman (ICDAR: Intelligent Cross-Data Analysis and Retrieval;, Chapter; Peer reviewed; Conference object, 2023)
      In order to take advantage of artificial intelligence (AI) solutions in endoscopy diagnostics, we must overcome the issue of limited annotations. These limitations are caused by the high privacy concerns in the medical ...

    • Meta-learning with implicit gradients in a few-shot setting for medical image segmentation 

      Khadka, Rabindra; Jha, Debesh; Riegler, Michael A.; Hicks, Steven; Thambawita, Vajira; Ali, Sharib; Halvorsen, Pål (Computers in Biology and Medicine;Volume 143, April 2022, 105227, Peer reviewed; Journal article, 2022-02-03)
      Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general application of any trained model is quite limited ...

    • 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 ...

    • A multi-centre polyp detection and segmentation dataset for generalisability assessment 

      Ali, Sharib; Jha, Debesh; Ghatwary, Noha; Realdon, Stefano; Cannizzaro, Renato; Salem, Osama E.; Lamarque, Dominique; Daul, Christian; Riegler, Michael Alexander; Ånonsen, Kim Vidar; Petlund, Andreas; Halvorsen, Pål; Rittscher, Jens; de Lange, Thomas; East, James E (Peer reviewed; Journal article, 2023)

    • Multimedia Datasets: Challenges and Future Possibilities 

      Nguyen, Thu; Storås, Andrea; Thambawita, Vajira L B; Hicks, Steven; Halvorsen, Pål; Riegler, Michael Alexander (Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Public multimedia datasets can enhance knowledge discovery and model development as more researchers have the opportunity to contribute to exploring them. However, as these datasets become larger and more multimodal, besides ...

    • Multimedia streaming analytics: quo vadis? 

      Midoglu, Cise; Avelino, Mariana; Gopalakrishnan, Shri Hari; Pham, Stefan; Halvorsen, Pål (MHV: Mile-High Video;MHV '22: Proceedings of the 1st Mile-High Video Conference, Conference object, 2022)
      In today’s complex OTT multimedia streaming ecosystem, the task of ensuring the best streaming experience to end-users requires extensive monitoring, and such monitoring information is relevant to various stakeholders ...

    • 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 ...

    • On evaluation metrics for medical applications of artificial intelligence 

      Hicks, Steven A.; Strumke, Inga; Thambawita, Vajira L B; Hammou, Malek; Riegler, Michael Alexander; Halvorsen, Pål (Scientific Reports;12, Article number: 5979 (2022), Peer reviewed; Journal article, 2022-04-08)
      Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. No single metric captures all the desirable properties of a model, which is why several metrics ...

    • 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). ...

    • Performance of data enhancements and training optimization for neural network: A polyp detection case study 

      Henriksen, Fredrik Lund; Jensen, Rune; Stensland, Håkon Kvale; Johansen, Dag; Riegler, Michael; Halvorsen, Pål (IEEE International Symposium on Computer-Based Medical Systems; 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), Conference object, 2019)
      Deep learning using neural networks is becoming more and more popular. It is frequently used in areas like video analysis, image retrieval, traffic forecast and speech recognition. In this respect, the learning and training ...

    • PMData: a sports logging dataset 

      Thambawita, Vajira; Hicks, Steven; Borgli, Hanna; Stensland, Håkon Kvale; Jha, Debesh; Svensen, Martin Kristoffer; Pettersen, Svein Arne; Johansen, Dag; Johansen, Håvard D.; Pettersen, Susann Dahl; Nordvang, Simon; Pedersen, Sigurd; Gjerdrum, Anders Tungeland; Grønli, Tor-Morten; Fredriksen, Per Morten; Eg, Ragnhild; Hansen, Kjeld S.; Fagernes, Siri; Claudi, Christine; Biørn-Hansen, Andreas; Dang Nguyen, Duc Tien; Kupka, Tomas; Hammer, Hugo Lewi; Jain, Ramesh; Riegler, Michael; Halvorsen, Pål (MM: International Multimedia Conference;MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference, Conference object, 2020-05-27)
      In this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our dataset enables the development of novel data analysis and machine-learning applications where, for ...

    • PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps 

      Fagereng, Jan Andre; Thambawita, Vajira L B; Storås, Andrea; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (Annual IEEE Symposium on Computer-Based Medical Systems;2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS), Conference object, 2022)
      Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) systems to detect polyps can improve detection ...

    • Polyps segmentation using synthetic images generated by GAN 

      Fagereng, Jan André (ACIT;2022, Master thesis, 2022)
      Early identification of polyps in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Multiple studies have shown that up to 28% of polyps might be missed during ...

    • Predicting peek readiness-to-train of soccer players using long short-term memory recurrent neural networks 

      Wiik, Theodor; Johansen, Håvard D.; Pettersen, Svein Arne; Matias Do Vale Baptista, Ivan Andre; Kupka, Tomas; Johansen, Dag; Riegler, Michael; Halvorsen, Pål (International Workshop on Content-Based Multimedia Indexing, CBMI;, Conference object, 2019)
      We are witnessing the emergence of a myriad of hardware and software systems that quantifies sport and physical activities. These are frequently touted as game changers and important for future sport developments. The vast ...

    • Prediction of schizophrenia from activity data using hidden Markov model parameters 

      Boeker, Matthias; Hammer, Hugo Lewi; Riegler, Michael; Halvorsen, Pål; Jakobsen, Petter (Peer reviewed; Journal article, 2022)

    • Real-time Analysis of Physical Performance Parameters in Elite Soccer 

      Andreassen, Kim Hartvedt; Johansen, Dag; Johansen, Håvard D.; Matias Do Vale Baptista, Ivan Andre; Pettersen, Svein Arne; Riegler, Micheal; Halvorsen, Pål (International Conference on Content-Based Multimedia Indexing (CBMI);, Conference object, 2019-10-21)
      Technology is having vast impact on the sports industry, and in particular soccer. All over the world, soccer teams are adapting digital information systems to quantify performance metrics. The goal is to assess strengths ...

    • Real-Time Detection of Events in Soccer Videos using 3D Convolutional Neural Networks 

      Rognved, Olav; Hicks, Steven; Lasantha Bandara Thambawita, Vajira; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael A.; Halvorsen, Pål (IEEE International Symposium on Multimedia; 2020 IEEE International Symposium on Multimedia (ISM), Chapter; Peer reviewed, 2020-01-22)
      In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D convolutional neural networks. The algorithm uses a sliding window approach to scan over a given video to detect events ...

    • 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 ...