Revisiting Prototypical Network for Cross Domain Few-Shot Learning-Reference-Cited by-同舟云学术

Revisiting Prototypical Network for Cross Domain Few-Shot Learning

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Zhou Fei¹,Wang Peng²,Zhang Lei¹,Wei Wei¹,Zhang Yanning¹

Affiliation:

1. Northwestern Polytechnical University

2. University of Wollonggong

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10204253.pdf?arnumber=10204253

Reference38 articles.

1. Meta-Learning With Differentiable Convex Optimization

2. Few-shot learning with graph neural networks;garcia;6th International Conference on Learning Representations ICLR,0

3. Model-agnostic meta-learning for fast adaptation of deep networks;finn;Proceedings of the 34th International Conference on Machine Learning-Volume,0

4. Learning to Compare: Relation Network for Few-Shot Learning

5. Hypertransformer: Model generation for supervised and semi-supervised few-shot learning;zhmoginov;International Conference on Machine Learning,0

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