What is image augmentation in deep learning?
An example of an AI chatbot conversation about image augmentation techniques in deep learning.
What is image augmentation in deep learning?
Image augmentation is a technique used to artificially expand the size of a training dataset by applying various transformations to the images.
What are some common techniques used for image augmentation?
Common techniques include rotation, flipping, scaling, cropping, and color adjustments.
How does image augmentation help improve model performance?
It helps by providing more diverse training data, which can reduce overfitting and improve the model's ability to generalize.
Are there any libraries that can help with image augmentation?
Yes, libraries like Keras, TensorFlow, and Albumentations offer built-in functions for image augmentation.
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