Research on small sample image classification based on auxiliary meta-learning

Huie Zhang; Mary Jane C. Samonte

doi:10.1117/12.3048282

3 October 2024 Research on small sample image classification based on auxiliary meta-learning

Huie Zhang, Mary Jane C. Samonte

Proceedings Volume 13272, Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024); 132720R (2024) https://doi.org/10.1117/12.3048282
Event: 5th International Conference on Computer Vision and Data Mining (ICCVDM 2024), 2024, Changchun, China

Abstract

In the field of computer vision, image classification is a very important branch, it‘s aims to classify different images into different category labels. Traditional image processing methods improve generalization ability and model accuracy by learning large amounts of data, but in practical applications, acquiring large amounts of labeled data is often very difficult and costly. Therefore, small sample Learning and meta-learning have become effective methods to solve this problem. This paper discusses its application in small sample image classification from the perspective of auxiliary meta-learning.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huie Zhang and Mary Jane C. Samonte "Research on small sample image classification based on auxiliary meta-learning", Proc. SPIE 13272, Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024), 132720R (3 October 2024); https://doi.org/10.1117/12.3048282

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