Self-supervised representation learning for surgical activity recognition.

Paysan, Daniel; Haug, Luis; Bajka, Michael; Oelhafen, Markus; Buhmann, Joachim M

Paysan, Daniel; Haug, Luis; Bajka, Michael; Oelhafen, Markus; Buhmann, Joachim M.

Afiliación

Paysan D; Department of Computer Science, ETH Zurich, Zurich, Switzerland. paysand@ethz.ch.
Haug L; Department of Computer Science, ETH Zurich, Zurich, Switzerland.
Bajka M; Division of Gynecology Department OB/GYN, University Hospital, Zurich, Switzerland.
Oelhafen M; VirtaMed AG, Schlieren, Switzerland.
Buhmann JM; Department of Computer Science, ETH Zurich, Zurich, Switzerland.

Int J Comput Assist Radiol Surg ; 16(11): 2037-2044, 2021 Nov.

Article en En | MEDLINE | ID: mdl-34542839

Asunto(s)

Aprendizaje Automático Supervisado; Humanos

Palabras clave

Deep Learning; Probabilistic modeling; Representation Learning; Self-supervised Learning; Surgical Activity Recognition; Unsupervised Learning

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Aprendizaje Automático Supervisado Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Int J Comput Assist Radiol Surg Asunto de la revista: RADIOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Suiza

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google