@inproceedings{20144ceeaa2d4e9ab6daaee35a6e3891,
title = "Few-Shot Classification with Cross-Feature Fusion",
abstract = "Most existing methods for few-shot image classification treat the support features and query features separately, and the category of a query image is determined based on its similarity to the support images. However, the relationships between the query features and support features are often ignored. In this paper, we propose a strategy that exploits the relationships between query and support features and give more weights to the highly related features. A cross-feature fusion method is further proposed to combine with metric learning to reduce overfitting. Extensive experiments on a wide range of datasets show that our method has achieved advanced results.",
keywords = "Few-shot classificaiton, cross-feature, query feature, similarity, support feature",
author = "Guohui Yao and Min Li and Dawei Song",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 8th International Conference on Computer and Communication Systems, ICCCS 2023 ; Conference date: 21-04-2023 Through 24-04-2023",
year = "2023",
doi = "10.1109/ICCCS57501.2023.10151269",
language = "English",
series = "2023 8th International Conference on Computer and Communication Systems, ICCCS 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "944--949",
booktitle = "2023 8th International Conference on Computer and Communication Systems, ICCCS 2023",
address = "United States",
}