NJUyued/MutexMatch4SSL
"MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization" by Yue Duan (TNNLS)
This project helps machine learning practitioners classify images more accurately, especially when they have only a small amount of labeled data but a lot of unlabeled images. You input your collection of images, some with labels (like 'cat' or 'dog') and many without. It then uses a clever technique to learn from both the labeled and unlabeled images, providing a model that can confidently classify new, unseen images.
Use this if you need to build a robust image classification model but are constrained by the cost or effort of labeling a large dataset.
Not ideal if you have abundant labeled data for your image classification task, as the benefits of semi-supervised learning would be less pronounced.
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Language
Python
License
MIT
Category
Last pushed
Nov 20, 2025
Commits (30d)
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