abdulfatir/prototypical-networks-tensorflow
Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
This project helps machine learning researchers and practitioners explore "few-shot learning" methods. You can input image datasets, like Omniglot or Mini-ImageNet, and it will output trained models that can classify new images even when they've only seen a few examples of each class. This is ideal for those working on computer vision tasks with limited data.
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Use this if you are a machine learning researcher or engineer interested in experimenting with prototypical networks for image classification where you have very little labeled data per class.
Not ideal if you need a production-ready, highly optimized, and thoroughly tested few-shot learning solution, as this is a research-oriented implementation that may contain bugs.
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Feb 09, 2018
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