Corpus ID: 220870675

Learning from Few Samples: A Survey

@article{Bendre2020LearningFF,
  title={Learning from Few Samples: A Survey},
  author={Nihar Bendre and H. Terashima-Mar{\'i}n and Peyman Najafirad},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.15484}
}
Deep neural networks have been able to outperform humans in some cases like image recognition and image classification. However, with the emergence of various novel categories, the ability to continuously widen the learning capability of such networks from limited samples, still remains a challenge. Techniques like Meta-Learning and/or few-shot learning showed promising results, where they can learn or generalize to a novel category/task based on prior knowledge. In this paper, we perform a… Expand

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