AIoT-MLSys-Lab/DeepAA
[ICLR 2022] "Deep AutoAugment" by Yu Zheng, Zhi Zhang, Shen Yan, Mi Zhang
This project helps machine learning engineers improve their image classification models by automatically finding the best data augmentation policies. You provide your image dataset, and it outputs an optimized set of image transformations (like rotations or color adjustments) that can make your model more accurate. This is for machine learning practitioners building and training computer vision models.
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Use this if you are a machine learning engineer working with image datasets and want to automatically enhance your model's performance through advanced data augmentation without manual trial-and-error.
Not ideal if you are looking for a general-purpose data augmentation library for non-image data or prefer to manually design your augmentation strategies.
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65
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3
Language
Python
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Last pushed
Sep 20, 2024
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