Few-Shot Learning With Enhancements to Data Augmentation and Feature Extraction

The few-shot image classification task is to enable a model to identify novel classes by using only a few labeled samples as references. In general, the more knowledge a model has, the more robust it is when facing novel situations. Although directly introducing large amounts of new training data to...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2024-06, Vol.PP, p.1-14
Hauptverfasser:	Zhang, Yourun, Gong, Maoguo, Li, Jianzhao, Feng, Kaiyuan, Zhang, Mingyang
Format:	Artikel
Sprache:	eng
Schlagworte:	Data augmentation Data models Feature extraction few-shot learning image classification Manifolds Task analysis Testing Training
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