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Multisource Deep Transfer Learning Based on Balanced Distribution Adaptation
The current traditional unsupervised transfer learning assumes that the sample is collected from a single domain. From the aspect of practical application, the sample from a single-source domain is often not enough. In most cases, we usually collect labeled data from multiple domains. In recent year...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9038385/ https://www.ncbi.nlm.nih.gov/pubmed/35479600 http://dx.doi.org/10.1155/2022/6915216 |