AbdulRahman M. A. Baraka

Joint-Embedding Predictive Architecture for Sensor-based Activity Recognition

The proposed Joint Embedding Predictive Architecture framework designed to learn robust and generalizable representations from unlabeled datasets demonstrates superior generalization on minority, high variance transitional activities such as sit-to-stand and sit-to-lie where supervised learning tend to overfit due to limited support.