![]() Augmentation both expands our training data and introduces heterogeneity in it thereby reducing the model’s tendency to overfit. Keep in mind, that these newly transformed images also belong to the same class as the original image. Image Data augmentation similarly is a technique where we expand our training dataset by creating modified versions of the images that already exist in our training data. Image Data Augmentationĭata augmentation is a method of increasing the size of our training data by transforming the data that we already have. We’ll understand what data augmentation is and how we can implement the same. This article will help you understand how you can expand your existing dataset through Image Data Augmentation in Keras TensorFlow with Python language. Limited training data can cause the model to overfit. Training deep convolutional neural networks on more data can lead to an increase in its performance and generalization capacity. ![]()
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December 2022
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