Blar i ODA Open Digital Archive på forfatter "Riegler, Michael"

Viser treff 41-51 av 51

    • SinGAN-Seg: Synthetic training data generation for medical image segmentation 

      Thambawita, Vajira L B; Salehi, Pegah; Sheshkal, Sajad Amouei; Hicks, Steven; Hammer, Hugo Lewi; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (PLOS ONE;17(5): e0267976, Peer reviewed; Journal article, 2022-05-02)
      Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a ...

    • Smittestopp analytics: Analysis of position data 

      Thambawita, Vajira L B; Hicks, Steven; Ewan, Jaouen; Halvorsen, Pål; Riegler, Michael (Simula SpringerBriefs on Computing;Volume 11, Chapter; Peer reviewed, 2022-06-18)
      Contact tracing applications generally rely on Bluetooth data. This type of data works well to determine whether a contact occurred (smartphones were close to each other) but cannot offer the contextual information GPS ...

    • Soccer athlete performance prediction using time series analysis 

      Ragab, Nourhan (ACIT;2022, Master thesis, 2022)
      Regardless of the sport you prefer, your favorite athlete has almost certainly disappointed you at some point. Did you jump to a conclusion and dismissed it as "not their day"? Or, did you consider the underlying causes for ...

    • Soccer highlight website design: Improving current interface and proposing universal design and accessibility principles. 

      Pranoto, Ernest (ACIT;2021, Master thesis, 2021)
      In today's increasingly technological world, all of the information we have are presented digitally through the internet, with a website as the main vehicle to deliver digital activities (Derong Lin et al, 2009). As the ...

    • Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children 

      Salehi, Pegah; Hassan, Syed Zohaib; Lammerse, Myrthe; Shafiee Sabet, Saeed; Riiser, Ingvild; Røed, Ragnhild Klingenberg; Sinkerud Johnson, Miriam; Hicks, Steven; Thambawita, Vajira; Powell, Martine; Lamb, Michael E.; Baugerud, Gunn Astrid; Halvorsen, Pål; Riegler, Michael (Big Data and Cognitive Computing;Volume 6 / Issue 2, Peer reviewed; Journal article, 2022-06-01)
      When responding to allegations of child sexual, physical, and psychological abuse, Child Protection Service (CPS) workers and police personnel need to elicit detailed and accurate accounts of the abuse to assist in ...

    • A Theoretical and Empirical Analysis of 2D and 3D Virtual Environments in Training for Child Interview Skills 

      Salehi, Pegah; Hassan, Syed Zohaib; Baugerud, Gunn Astrid; Powell, Martine; Johnson, Miriam S.; Johansen, Dag; Shafiee Sabet, Saeed; Riegler, Michael; Halvorsen, Pål (Peer reviewed; Journal article, 2024)
      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 ...

    • Toadstool: a dataset for training emotional intelligent machines playing Super Mario Bros 

      Svoren, Henrik; Thambawita, Vajira; Halvorsen, Pål; Jakobsen, Petter; Garcia-Ceja, Enrique; Noori, Farzan Majeed; Hammer, Hugo Lewi; Lux, Mathias; Riegler, Michael; Hicks, Steven (MMSys: Multimedia Systems;MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference, Conference object, 2020)
      Games are often defined as engines of experience, and they are heavily relying on emotions, they arouse in players. In this paper, we present a dataset called Toadstool as well as a reproducible methodology to extend ...

    • Unraveling the Impact of Land Cover Changes on Climate Using Machine Learning and Explainable Artificial Intelligence 

      Kolevatova, Anastasiia; Riegler, Michael; Cherubini, Francesco; Hu, Xiangping; Hammer, Hugo Lewi (Big Data and Cognitive Computing;Volume 5, Issue 4, Peer reviewed; Journal article, 2021-10-15)
      A general issue in climate science is the handling of big data and running complex and computationally heavy simulations. In this paper, we explore the potential of using machine learning (ML) to spare computational time ...

    • Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis 

      Storås, Andrea; Andersen, Ole Emil; Lockhart, Sam; Thielemann, Roman; Gnesin, Filip; Thambawita, Vajira L B; Hicks, Steven; Kanters, Jørgen K.; Strumke, Inga; Halvorsen, Pål; Riegler, Michael (Peer reviewed; Journal article, 2023)
      Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide ...

    • VISEM: A Multimodal Video Dataset of Human Spermatozoa 

      Haugen, Trine B.; Hicks, Steven; Andersen, Jorunn Marie; Witczak, Oliwia; Hammer, Hugo Lewi; Borgli, Rune Johan; Halvorsen, Pål; Riegler, Michael (ACM MMSys conference series;, Chapter; Peer reviewed, 2019)
      Real multimedia datasets that contain more than just images or text are rare. Even more so are open multimedia datasets in medicine. Often, clinically related datasets only consist of image or videos. In this paper, we ...

    • Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations 

      Hicks, Steven; Storås, Andrea; Riegler, Michael; Midoglu, Cise; Hammou, Malek; Lange, Thomas de; Parasa, Sravanthi; Halvorsen, Pål; Strumke, Inga (Peer reviewed; Journal article, 2024)
      Deep learning has achieved immense success in computer vision and has the potential to help physicians analyze visual content for disease and other abnormalities. However, the current state of deep learning is very much a ...