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Data Augmentation in Computer Vision for Self Supervised Learning
Data augmentation is just a process to like basically perturb the data or like augment the data. And so it has played a fundamental role for computer vision for self supervised learning and contrastive learning. The way most of the current methods work contrastive or otherwise is by taking an image, in the case of images is by computing two perturbations of it. So now you can use a variety of different ways to enforce this constraint,. Like these features being similar, you can do this by contrastivelearning.