Blar i Fakultet for informasjonsteknologi og elektroteknikk (IE) på forfatter "Ihlen, Espen Alexander F."

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    • Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk 

      Groos, Daniel; Adde, Lars; Aubert, Sindre Aarnes; Boswell, Lynn; De Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-Spira, Deborah; Haukeland, Andreas; Loennecken, Marianne; Msall, Michael; Moinichen, Unn Inger; Pascal, Aurelie; Peyton, Colleen; Ramampiaro, Heri; Schreiber, Michael D.; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Thomas, Niranjan; van den Broeck, Christine; Øberg, Gunn Kristin; Ihlen, Espen Alexander F.; Støen, Ragnhild (Peer reviewed; Journal article, 2022)
      Importance Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity. Objective ...

    • Skeleton Based Cerebral Palsy Diagnosis using Deep Learning and Attention 

      Vold, Martin (Master thesis, 2020)
      Dyp læring har i de siste årene oppnådd gode resultater innen forskningsfelt som datasyn og menneskelig aktivitets gjenkjenning. Innen medisin har disse gjennombruddene åpnet nye dører for hvordan problemer blir løst og ...

    • Towards human-level performance on automatic pose estimation of infant spontaneous movements 

      Groos, Daniel; Adde, Lars; Støen, Ragnhild; Ramampiaro, Heri; Ihlen, Espen Alexander F. (Peer reviewed; Journal article, 2021)
      Assessment of spontaneous movements can predict the long-term developmental disorders in high-risk infants. In order to develop algorithms for automated prediction of later disorders, highly precise localization of segments ...