Data Augmentation Purpose

Easy

neural-networks Tesla Waymo Snap

How does data augmentation (e.g., random cropping, flipping, color jitter) help improve the generalization of a neural network?

Multiple Choice

It increases the effective size and diversity of the training set, reducing overfitting It allows the network to learn faster by presenting easier examples first It corrects class imbalance by generating synthetic minority samples It reduces the resolution of images so the network trains more quickly

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Data Augmentation Purpose

Multiple Choice

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