The primary purpose of data augmentation in computer vision tasks is to increase the size and diversity of the training dataset without actually collecting new data. Data augmentation involves applying various transformations to existing images, such as rotations, flips, scaling, cropping, and adding noise, to create new, synthetic images. This helps to improve the generalization ability of the model and reduce....
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