GAN-Based Skeleton Fall Detection Data Augmentation Pipeline

상황

A skeleton-based fall detection dataset is limited; a GAN augments synthetic skeleton sequences to improve classifier performance.

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Split dataset into train/test sets

Accept generated samples via discriminator realism check

Adjust GAN parameters if classifier performance does not improve

Deploy model after performance gain

Reusable when training data for rare fall events is scarce and synthetic motion generation is needed.