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Synthetic Data Generation for Computer Vision Models
In computer vision, generating synthetic data through perturbations of existing images allows for the creation of diverse data with minimal original data points. This synthesis enables robustness and fine-tuning of models with relatively low data requirements. This approach reduces the need for large datasets and instead focuses on generating high-quality examples, significantly enhancing model training and performance with a smaller number of data points.