Efficient Post-Training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments

The author proposes an automated augmentation flow to convert existing models into Early Exit Neural Networks (EENNs) for improved efficiency in heterogeneous or distributed hardware targets.