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Few-shot Learning with a Universal Template (FLUTE)

Pattern for Efficient Learning: A training method for few-shot learning in computer vision.

Getting high accuracy out of a classifier trained on a small number of examples is tricky. You might train the model on several large-scale datasets prior to few-shot training, but what if the few-shot dataset includes novel classes? A new method performs well even in that case.

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