Unsupervised Black-Box Model Domain Adaptation for Brain Tumor Segmentation

Unsupervised domain adaptation (UDA) is an emerging technique that enables the transfer of domain knowledge learned from a labeled source domain to unlabeled target domains, providing a way of coping with the difficulty of labeling in new domains. The majority of prior work has relied on both source...

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Detalles Bibliográficos
Autores principales: Liu, Xiaofeng, Yoo, Chaehwa, Xing, Fangxu, Kuo, C.-C. Jay, El Fakhri, Georges, Kang, Je-Won, Woo, Jonghye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201342/
https://www.ncbi.nlm.nih.gov/pubmed/35720708
http://dx.doi.org/10.3389/fnins.2022.837646

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201342/
https://www.ncbi.nlm.nih.gov/pubmed/35720708
http://dx.doi.org/10.3389/fnins.2022.837646

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