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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10756649/ |
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