Iterative joint classifier and domain adaptation for visual transfer learning

Current available supervised classifiers cannot generalize across various domains due to distribution mismatch among them. Domain adaptation and transfer learning algorithms are proposed to tackle domain shift problem that originates from different data collection conditions. In this paper, we propo...

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Detalles Bibliográficos
Autores principales: Noori Saray, Shiva, Tahmoresnezhad, Jafar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479271/
https://www.ncbi.nlm.nih.gov/pubmed/34603538
http://dx.doi.org/10.1007/s13042-021-01428-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479271/
https://www.ncbi.nlm.nih.gov/pubmed/34603538
http://dx.doi.org/10.1007/s13042-021-01428-z

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