Low-cost multi-core on-chip learning schemes

Nowadays, to reduce the dependence of devices on cloud servers, machine learning workloads are required to process data on the edge. Furthermore, to improve adaptability to uncontrolled environments, there is a growing need for on-chip learning. Limitations in power and area for edge devices have increased interest in low-cost neural network...

Event-Driven Graph Neural Network Accelerators for Low-Power Vision

Event-based cameras promise new opportunities for smart vision systems deployed at the edge. Contrary to their conventional frame-based counterparts, event-based cameras generate temporal light intensity changes as events on a per-pixel basis, enabling ultra-low latency with microsecond-scale temporal resolution, low power consumption at...