2023
DOI: 10.3390/app132312843
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A Large-Class Few-Shot Learning Method Based on High-Dimensional Features

Jiawei Dang,
Yu Zhou,
Ruirui Zheng
et al.

Abstract: Large-class few-shot learning has a wide range of applications in many fields, such as the medical, power, security, and remote sensing fields. At present, many few-shot learning methods for fewer-class scenarios have been proposed, but little research has been performed for large-class scenarios. In this paper, we propose a large-class few-shot learning method called HF-FSL, which is based on high-dimensional features. Recent theoretical research shows that if the distribution of samples in a high-dimensional… Show more

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