NC$$^2$$E: boosting few-shot learning with novel class center estimation-Reference-Cited by-同舟云学术

NC$$^2$$E: boosting few-shot learning with novel class center estimation

Published:2022-12-05 Issue:9 Volume:35 Page:7049-7062
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Wu Zheng,Shen Changchun,Guo Kehua^ORCID,Luo Entao,Wang Liwei

Funder

National Social Science Fund of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-08080-w.pdf

Reference46 articles.

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2. Chen WY, Liu YC, Kira Z, et al (2019) A closer look at few-shot classification. In: International conference on learning representations (ICLR). https://openreview.net/forum?id=HkxLXnAcFQ

3. Chen Z, Fu Y, Zhang Y et al (2019) Multi-level semantic feature augmentation for one-shot learning. IEEE Trans Image Process (TIP) 28(9):4594–4605. https://doi.org/10.1109/TIP.2019.2910052

4. Das D, Lee CSG (2020) A two-stage approach to few-shot learning for image recognition. IEEE Trans Image Process (TIP) 29:3336–3350. https://doi.org/10.1109/TIP.2019.2959254

5. Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1–30. https://doi.org/10.5555/1248547.1248548

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