Face Recognition System

Face Recognition System

EDOM Reference Design
Face Recognition System
We leverage EDOM carried products into face recognition system. For deep learning technology, we use NVIDIA TensorRT for efficiently deploying neural networks onto the embedded platform, improving performance and power efficiency using graph optimizations, kernel fusion, and half-precision FP16 on the Jetson.
Face Recognition System
1. Real-time multiple faces recognition
2. Max-Q low power consumption < 7.5W
3. Pure AI application at the edge device
  • CMOS Image Sensor

    CMOS Image Sensor

    This image sensor is equipped with an LED flicker mitigation (LFM) function that reduces flickering when shooting LED signs and traffic signals, as well as High Dynamic Range (HDR) function capable of 120 dB2 wide dynamic range shooting.

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  • Jetson TX2 Module

    Jetson TX2 Module

    This is an AI supercomputer on a module, powered by NVIDIA Pascal™ architecture. Best of all, it packs this performance into a small, power-efficient form factor that’s ideal for intelligent edge devices like robots, drones, smart cameras, and portable medical devices. It supports all the features of the Jetson TX1 module while enabling bigger, more complex deep neural networks.

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  • Jetson TX1 Module

    Jetson TX1 Module

    This AI supercomputer features NVIDIA Maxwell™ architecture, 256 NVIDIA CUDA® cores, 64-bit CPUs, and a power-efficient design. Plus, it includes the latest technology for deep learning, computer vision, GPU computing, and graphics—making it ideal for embedded AI computing.

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  • Jetson TX2 Developer Kit

    Jetson TX2 Developer Kit

    This kit highlights the hardware capabilities and interfaces of the Jetson TX2 board, comes with design guides and documentation, and is pre-flashed with a Linux development environment. It also supports the NVIDIA Jetpack SDK, which includes the ....

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