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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2021
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| Materias: | |
| 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 |