Blar i SINTEF Digital på forfatter "Garcia-Ceja, Enrique"

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    • Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls 

      Jakobsen, Petter; Garcia-Ceja, Enrique; Riegler, Michael; Stabell, Lena Antonsen; Nordgreen, Tine; Tørresen, Jim; Fasmer, Ole Bernt; Ødegaard, Ketil Joachim (Peer reviewed; Journal article, 2020)
      Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner ...

    • Designing a Modeling Language for Customer Journeys: Lessons Learned from User Involvement 

      Halvorsrud, Ragnhild; Boletsis, Costas; Garcia-Ceja, Enrique (Chapter; Peer reviewed, 2021)
      Although numerous methods have been formalized for handling the technical aspects of developing domain-specific modeling languages (DSMLs), user needs and usability aspects are often addressed in ad hoc manners and late ...

    • Frameworks for data-driven quality management in cyber-physical systems for manufacturing: A systematic review 

      Cassoli, Beatriz; Jourdan, Nicolas; Nguyen, Phu Hong; Sen, Sagar; Garcia-Ceja, Enrique; Metternich, Joachim (Peer reviewed; Journal article, 2022)
      Recent advances in the manufacturing industry have enabled the deployment of Cyber-Physical Systems (CPS) at scale. By utilizing advanced analytics, data from production can be analyzed and used to monitor and improve the ...

    • HTAD: A Home-Tasks Activities Dataset with Wrist-Accelerometer and Audio Features 

      Garcia-Ceja, Enrique; Thambawita, Vajira L B; Hicks, Steven; Jha, Debesh; Jakobsen, Petter; Hammer, Hugo Lewi; Halvorsen, Pål; Riegler, Michael (Peer reviewed; Journal article, 2021)
      In this paper, we present HTAD: A Home Tasks Activities Dataset. The dataset contains wrist-accelerometer and audio data from people performing at-home tasks such as sweeping, brushing teeth, washing hands, or watching TV. ...

    • HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy 

      Borgli, Hanna; Thambawita, Vajira; Smedsrud, Pia H; Hicks, Steven; Jha, Debesh; Eskeland, Sigrun Losada; Randel, Kristin Ranheim; Pogorelov, Konstantin; Lux, Mathias; Dang Nguyen, Duc Tien; Johansen, Dag; Griwodz, Carsten; Stensland, Håkon Kvale; Garcia-Ceja, Enrique; Schmidt, Peter T; Hammer, Hugo Lewi; Riegler, Michael; Halvorsen, Pål; de Lange, Thomas (Peer reviewed; Journal article, 2020)
      Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to ...

    • On The Reliability Of Machine Learning Applications In Manufacturing Environments 

      Jourdan, Nicolas; Sen, Sagar; Husom, Erik Johannes; Garcia-Ceja, Enrique; Biegel, Tobias; Metternich, Joachim (Chapter, 2021)
      The increasing deployment of advanced digital technologies such as Internet of Things (IoT) devices and Cyber-Physical Systems (CPS) in industrial environments is enabling the productive use of machine learning (ML) ...

    • A Systematic Mapping Study on Approaches for AI-Supported Security Risk Assessment 

      Erdogan, Gencer; Garcia-Ceja, Enrique; Hugo, Åsmund Pedersen; Nguyen, Phu Hong; Sen, Sagar (Chapter; Peer reviewed, 2021)
      Effective assessment of cyber risks in the increasingly dynamic threat landscape must be supported by artificial intelligence techniques due to their ability to dynamically scale and adapt. This article provides the state ...