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Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery
In this article, we consider a version of the challenging problem of learning from datasets whose size is too limited to allow generalisation beyond the training set. To address the challenge, we propose to use a transfer learning approach whereby the model is first trained on a synthetic dataset re...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469565/ https://www.ncbi.nlm.nih.gov/pubmed/34573765 http://dx.doi.org/10.3390/e23091140 |