Realtime Facial Expression Recognition: Neuromorphic Hardware vs. Edge AI Accelerators

arXiv:2403.08792v1 Announce Type: cross
Abstract: The paper focuses on real-time facial expression recognition (FER) systems as an important component in various real-world applications such as social robotics. We investigate two hardware options for the deployment of FER machine learning (ML) models at the edge: neuromorphic hardware versus edge AI accelerators. Our study includes exhaustive experiments providing comparative analyses between the Intel Loihi neuromorphic processor and four distinct edge platforms: Raspberry Pi-4, Intel Neural Compute Stick (NSC), Jetson Nano, and Coral …

abstract accelerators ai accelerators applications arxiv cs.cv cs.lg cs.ne cs.pf deployment edge edge ai hardware machine machine learning neuromorphic paper real-time realtime recognition robotics social systems the edge type world