GAN Experiments for Synthetic Acceleration Data Generation #17
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Pull Request Description
This update introduces a new folder containing early experiments with Generative Adversarial Networks (GANs) aimed at generating synthetic acceleration data from raw Open Seizure Database (OSDB) recordings.
Key Contributions:
Developed GAN models to explore the feasibility of generating synthetic time-series data from OSDB acceleration data.
Focused on leveraging high-certainty, high-integrity labeled time steps to create synthetic labels with lower uncertainty.
Aims to improve training efficiency and model performance for seizure detection.