Cristin-person-ID: 810287
Person

Daniel Groos

  • Stilling:
    Stipendiat
    ved Institutt for nevromedisin og bevegelsesvitenskap ved Norges teknisk-naturvitenskapelige universitet

Klassifisering

Vitenskapsdisipliner

Medisinsk teknologi

Emneord

Deep learning • Nevrale nettverk • Maskinlæring • Kunstig intelligens • Datasyn

Region

  • Norden

Land

  • Norge

Kontaktinformasjon

Resultater Resultater

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 mfl.. 2022, JAMA Network Open. UIT, ANN, UG, STOLAV, UNN, NU, UoC, NTNU, OUS, INDIAVitenskapelig artikkel

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

Groos, Daniel; Adde, Lars; Støen, Ragnhild; Ramampiaro, Heri; Ihlen, Espen Alexander F.. 2022, Computerized Medical Imaging and Graphics. STOLAV, NTNUVitenskapelig artikkel

Fully automated clinical movement analysis from videos using skeleton-based deep learning.

Groos, Daniel; Adde, Lars; Aubert, Sindre Aarnes; Haukeland, Andreas; Ramampiaro, Heri; Støen, Ragnhild; Ihlen, Espen Alexander F.. 2021, Gait & Posture. NTNUSammendrag/abstract

Fully automated clinical movement analysis from videos using skeleton-based deep learning.

Groos, Daniel; Adde, Lars; Aubert, Sindre Aarnes; Haukeland, Andreas; Ramampiaro, Heri; Støen, Ragnhild; Ihlen, Espen Alexander F.. 2021, ESMAC 2021. NTNUVitenskapelig foredrag
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Utmerkelser

  • 2018 - Norwegian Open AI Lab Master Thesis Awards - Application Award - Runner-up