TMNIO:Triplet merged network with involution operators for improved few‐shot image classification

Abstract Few‐shot learning enables machines to learn efficiently from limited labelled data. However, existing few‐shot learning methods may perform poorly when there is a lack of sufficient samples, and may encounter problems such as domain shift or overfitting when applied to new domains or tasks....

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Bibliografiske detaljer

Principais autores:	Qi Lulu, Xu Ranhui, Zhao Shaojie, Zheng Mingming, Yu Weiqin
Format:	Artigo
Sprog:	Inglês
Udgivet:	Wiley 2024-05-01
Serier:	IET Image Processing
Fag:	image classification few‐shot learning contrastive learning prototypical networks
Online adgang:	https://doi.org/10.1049/ipr2.13055
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