Facial Recognition for Access Control and Time & Attendance Systems
TOPICS COVERED
- Synthetic Data Training: Solving the GDPR Compliance Gap
- NPU Performance: Ethos-U65 vs. i.MX 8M Plus Benchmarks
- Presentation Attack Detection (PAD): Defending Against Spoofing
- Edge Deployment: Optimizing Neural Networks for Embedded Hardware
Embedded facial recognition with NXP i.MX 93 delivers fast, secure access control using synthetic data and PAD.
Move beyond easily forgotten keys and access codes with a biometric system designed for the modern regulatory landscape. This solution tackles the “privacy problem” by using synthetic datasets—computer-generated faces that mimic real-world diversity without compromising individual privacy or violating data protection laws. Powered by the Ethos U65 NPU, the system delivers lightning-fast recognition and advanced deception detection. Whether verifying identity at a high-security portal or managing employee clock-ins, this technology ensures only authorized individuals gain entry while maintaining a robust defense against spoofing attempts using photos, videos, or masks.
Move beyond easily forgotten keys and access codes with a biometric system designed for the modern regulatory landscape. This solution tackles the “privacy problem” by using synthetic datasets—computer-generated faces that mimic real-world diversity without compromising individual privacy or violating data protection laws. Powered by the Ethos U65 NPU, the system delivers lightning-fast recognition and advanced deception detection. Whether verifying identity at a high-security portal or managing employee clock-ins, this technology ensures only authorized individuals gain entry while maintaining a robust defense against spoofing attempts using photos, videos, or masks.
Key Takeaways:
- Synthetic data training
- Fast i.MX 93 inference
- Built‑in spoof detection
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