2021
DOI: 10.3906/elk-2102-101
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A hybrid approach based on transfer and ensemble learning for improving performances of deep learning models on small datasets

Abstract: The need for high-volume data is one of the challenging requirements of the deep learning methods and it makes it harder to apply deep learning algorithms to domains in which the data sources are limited, in other words small. These domains may vary from medical diagnosis to satellite imaging. The performances of the deep learning methods on small datasets can be improved by the approaches such as data augmentation, ensembling, and transfer learning. In this study, we propose a new approach that utilizes trans… Show more

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