Xnor's Face Recognition on Embedded Devices

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Bring Face Recognition to your Edge Devices

Benefits of Xnor’s Face Recognition Technology

Scalability

Identify multiple faces quickly and accurately for scenarios ranging from home and commercial security to retail and consumer devices.

Security

Attention awareness and other built-in safeguards foil spoofing attempts like using a photograph or a 3D replica of a person’s face.

Commodity Hardware

Add face recognition capabilities to existing products without needing to upgrade or change hardware.

On-Device Training

Our deep learning models allow you to create self-contained solutions that can learn new faces with as few as 3 images - without cloud-based resources.

Privacy

Face recognition signatures are stored as binary data so they can’t be reverse-engineered.

Speed

Perform complex AI tasks 10x faster than AI solutions that require a GPU or neural accelerator.

Contact Xnor to learn more about how you can incorporate the next generation of AI into your products.

The Advantage of Xnor’s AI at the Edge

Other solutions require expensive mobile processors or a neural or GPU accelerator. Xnor’s AI at the Edge allows you to run face recognition models and train new faces without accessing a cloud-based data center. This is not only faster, but significantly more secure since data doesn’t have to be sent out.

Utilizing Xnor’s breakthrough research in computer vision, face recognition only requires the CPU of very small compute platforms, and can be trained to identify new faces completely on-device.

This makes the solution autonomous - no need to rely on a cloud connection or risk downtime with network and service outages.

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