KentaItakura/Data-Augmentation-using-Mix-up-with-Custom-Training-Loop-with-MATLAB
Data Augmentation using Mix-up with Custom Training Loop
This project helps image recognition practitioners improve the accuracy of their classification models, especially when they have limited training data. It takes existing image datasets and generates new, synthetic training images by blending pairs of existing images. The output is a more robust image classification model ready for deployment, used by scientists, engineers, or anyone working with image data in MATLAB.
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Use this if you are a deep learning practitioner using MATLAB for image classification and want to improve model performance by expanding your training dataset through a technique called 'mix-up' data augmentation.
Not ideal if you are not working with image classification tasks, do not use MATLAB for your deep learning projects, or are looking for data augmentation methods other than mix-up.
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Language
MATLAB
License
BSD-3-Clause
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Last pushed
Jan 26, 2022
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