Semi-Supervised Support Vector Machine for Digital Twins Based Brain Image Fusion

The purpose is to explore the feature recognition, diagnosis, and forecasting performances of Semi-Supervised Support Vector Machines (S3VMs) for brain image fusion Digital Twins (DTs). Both unlabeled and labeled data are used regarding many unlabeled data in brain images, and semi supervised suppor...

Descripción completa

Detalles Bibliográficos
Autores principales: Wan, Zhibo, Dong, Youqiang, Yu, Zengchen, Lv, Haibin, Lv, Zhihan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8298822/
https://www.ncbi.nlm.nih.gov/pubmed/34305523
http://dx.doi.org/10.3389/fnins.2021.705323

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8298822/
https://www.ncbi.nlm.nih.gov/pubmed/34305523
http://dx.doi.org/10.3389/fnins.2021.705323

Ejemplares similares