Facial recognition is one of the most popular non-invasive security technologies in use, given the ever-present threats in both the physical and cyber world. Although facial recognition systems has seen tremendous growth, the technology has been hampered by cost and energy consumption limitations. Real-time training and inference of faces require huge computing power, typically using high-end and power-hungry CPU (central processing unit), GPUs (graphics processing units) or SoCs (system on a chip). The threat of cyber-hacking the stored facial bio-data is also real, as these digital data remain housed in IT server infrastructure.
This technology is based on a hardware implementation of Artificial Neural Networks, offering a low power, low cost and secure multi platform module. No software is required, and the architecture allows dynamic learning-on-the-fly.