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Face Recognition Intelligent Server

> Adopt advanced face deep learning algorithm, and give full play to GPU parallel computing processing capability. Algorithm recognition effect and practical performance have reached advanced level in the industry.
> Adopt advanced clustering algorithm, so clustering is more accurate.
> Arm the restricted list database which has millions of face data.
> Adopt multiple slot design.
> Support modular replacement, which better meets requirements of changing the hardware.
> Support cloud deployment.

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  • System

    Main processor

    Two Intel Xeon Gold 5120



    Operating system

    CentOS Linux release 7.4.1708 (Core)


    Sixteen 16GB DDR4 memory, maximum 24 slots.


    Five 3.5”4T disks which can be extended to maximum 32T (each disk is 4T), and maximum 8 slots.
    7.2K RPM SATA 6Gbps 512n 3.5”

    AI for Face Analysis

    Face Detection

    Detect and analyze face image stream, including gender, age, expression, glasses, mustache, mouth mask, open and closed eyes. Support jpg, png, bmp, jfif, dib, tif, jpe, pbm, ppm, and pgm pictures.

    Face Modeling

    Extract face image features.

    Face Arming

    Compare the face snapshot with designated face database in real-time, and get information about the first person that exceeds arm thresholds.

    Search History Alarm Records

    Search historical deployment alarm records.

    Registered Database Management

    Distinguish restricted list database, trusted list database, static database and other databases.
    Add, delete and modify the databases.
    Add, delete and modify the database members.

    Search Registered Database

    Search registered database member by name, gender, birthday and identity card number.

    Search by Image in Registered Database

    Select one face image manually, compare with registered database, thus find the qualified personnel, and arrange them according to the similarity.

    Search Snapshot Database

    Search historical person passing by records in the snapshot database.

    Search by Image in Snapshot Database

    Select one face image manually, filter by time and channel, compare with historical data, thus find the qualified personnel, and arrange them according to the similarity.


    Support 1V1 face comparison, and return similarity result.

    Face Clustering

    Support face clustering and archives, and work with Video Cloud Platform, so multiple faces of one person cluster as one archive; identity verification and other face related applications.


    Support cluster (in case of deployment of video cloud child node).



    Two 10000/1000 MB self-adaptive network ports


    2 front USB3.0 ports and 3 rear USB3.0 ports


    2 VGA ports

    Other Ports

    1 RJ-45 management network port


    Power Supply

    100–127V/200–240V, 50/60Hz, 10A/5A

    Power Redundancy

    Dual power redundancy

    Power Consumption

    ≤ 800W

    Operating Temperature

    10°C to 35°C (50°F to 95°F )

    Operating Humidity

    35%–80% RH, maximum relative humidity is 90%RH (40°C ).

    Storage Temperature

    -40°C to 60°C (-40°F to 140°F)

    Storage Humidity


    Gross Weight

    31.89 kg (70.31 lbs)

    Net Weight

    22.09 kg (48.70 lbs)


    87.00mm × 447.60 mm × 735.60 mm

    (3.43" × 17.62" × 28.96")

    Package Dimensions

    273.00mm × 754.00mm × 1069.00mm

    (10.75" × 29.68" × 42.09")


    Standard 19” rack installation with guide rail.