cxm12/UNiFMIR
Pretraining a foundation model for generalizable fluorescence microscopy-based image restoration
This project helps scientists and researchers improve the quality of their fluorescence microscopy images. It takes blurry, noisy, or low-resolution microscopy images and transforms them into clearer, sharper, and higher-resolution versions. This tool is designed for biologists, microscopists, and lab technicians who work with optical microscopy.
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Use this if you need to restore or enhance fluorescence microscopy images for better visualization, analysis, or publication, especially across different types of image restoration tasks like denoising or super-resolution.
Not ideal if you are working with other types of images outside of fluorescence microscopy, or if you need to train a model from scratch without existing foundational models.
Stars
65
Forks
5
Language
Python
License
GPL-3.0
Category
Last pushed
Apr 24, 2024
Commits (30d)
0
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curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/cxm12/UNiFMIR"
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