chenhaoxing/SSFormers
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning" (SCIENCE CHINA Information Sciences).
This project helps machine learning practitioners classify images accurately, even when they have very few examples for a new category. You provide a small set of labeled images for new categories, and the system outputs a model capable of recognizing those new categories. This is ideal for AI researchers or developers building image recognition systems in data-scarce environments.
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Use this if you need to perform image classification on new categories with extremely limited training data per category.
Not ideal if you have abundant labeled data for all your image categories or if your primary need is not few-shot image classification.
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Language
Python
License
MIT
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Last pushed
Jul 29, 2023
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