How to use Data Augmentation when you have limited data

One of the most common problems in Computer Vision is the lack of images when training ML models. In deep learning, a large amount of data is required to make neural networks to learn relevant characteristics of inputs and then to perform the inference process correctly.

Throughout the following whitepaper that you can download, we will see in detail the methods used, some simple and some more complex, to produce synthetic images needed in the training of computer vision models.

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