A Survey on Cross-Domain Few-Shot Image Classification

Author:

Deng Shisheng,Liao Dongping,Gao Xitong,Zhao Juanjuan,Ye Kejiang

Publisher

Springer Nature Switzerland

Reference70 articles.

1. Adler, T., et al.: Cross-domain few-shot learning by representation fusion. arXiv preprint arXiv:2010.06498 (2020)

2. Ammour, N., Bashmal, L., Bazi, Y., Al Rahhal, M.M., Zuair, M.: Asymmetric adaptation of deep features for cross-domain classification in remote sensing imagery. IEEE Geosci. Remote Sens. Lett. 15(4), 597–601 (2018)

3. Blanchard, G., Lee, G., Scott, C.: Generalizing from several related classification tasks to a new unlabeled sample. In: Advances in Neural Information Processing Systems, vol. 24 (2011)

4. Cai, J., Shen, S.M.: Cross-domain few-shot learning with meta fine-tuning. arXiv preprint arXiv:2005.10544 (2020)

5. Chaudhari, S., Mithal, V., Polatkan, G., Ramanath, R.: An attentive survey of attention models. ACM Trans. Intell. Syst. Technol. (TIST) 12(5), 1–32 (2021)

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