Self-Supervison with data-augmentation improves few-shot learning

Author:

Kumar PrashantORCID,Toshniwal DurgaORCID

Publisher

Springer Science and Business Media LLC

Reference62 articles.

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2. Gidaris S, Bursuc A, Komodakis N, Pérez P, Cord M (2019) Boosting few-shot visual learning with self-supervision. In: Proceedings of the IEEE/CVF international conference on computer vision, pp 8059–8068

3. Snell J, Swersky K, Zemel R (2017) Prototypical networks for few-shot learning. Advances in neural information processing systems 30

4. Lee K, Maji S, Ravichandran A, Soatto S (2019) Meta-learning with differentiable convex optimization. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 10657–10665

5. Ren M, Triantafillou E, Ravi S, Snell J, Swersky K, Tenenbaum JB, Larochelle H, Zemel RS (2018) Meta-learning for semi-supervised few-shot classification. arXiv:1803.00676

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