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Few-Shot Classification Study for Prototype Fusion and Completion

Deep learning models face significant challenges in image classification due to the limited availability of training samples. To address this issue, few-shot learning, which enables model training with a small number of samples, has emerged. When applied to classification tasks, it is referred to as...

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Hlavní autoři: Yuheng Wang, Yanguo Sun, Zhenping Lan, Nan Wang, Jiansong Li, Xincheng Yang
Médium: Artigo
Jazyk:Inglês
Vydáno: IEEE 2024-01-01
Edice:IEEE Access
Témata:
Deep learning
few-shot classification
prototype network
prototype completion
prototype fusion
On-line přístup:https://ieeexplore.ieee.org/document/10756649/
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