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AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use
  • AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use
  • AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use
  • AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use
  • AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use
  • AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use

AI smart face recognition module T210 high recognition rate, low power consumption, offline living body recognition, serial communication easy to use

Attendance system, access control system, smart door lock, safe, locker, member management, mobile payment PageView : 3151

Smart AI offline face recognition module

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    Product Description

    PRODUCT DESCRIPTION

    ·The module main control adopts RISC-V dual-core 64-bit CPU, with the highest possible        Up to 1 TOPS computing power, CPU power consumption is only 0.3W;
       ·The module is concise, the size is small, only 25.4*25.4*2.60 mm;        Built-in Al face recognition algorithm and model library, start super fast; ARM,        8 and 32-bit microcontrollers such as MSC51 can be easily driven with very few drive codes;
       ·The module has a wide range of applications and can be used in time and attendance systems, access control systems, smart door locks,        Safe, locker, member management, mobile payment, smart front desk, people        Face verification, device security login, etc.

    Product Image

    PRODUCT PICTURES

(Module-Front)
(Module-back)

(Beta-front)

(Beta-back)



Product hardware

Kernel

RISC-V Dual Core 64bit,with FPU

Main frequency

400MHz/overclockable to 600MHz

SRAM

Built-in 8M Byte

Image Identification

QVGA@60fps/VGA@30fps

Speech Recognition

Microphone array(8mics)

Network model

Support YOLOv3/Mobilenetv2/TinyYOLOv2/face recognition, etc.

Deep learning framework

Support mainstream frameworks such as TensorFlow/Keras/Darknet/Caffe

Peripheral interface

FPIOA/UART/GPIO/SPI/I2C/I2S/TIMER 

Video processing

Neural Network Processor KPU

FPU meets IEEE754-2008 standard

Audio processor APU

Fast Fourier Transform Accelerator FFT

Other parameters

Template scheme

Kanzhi K210

Sheet parameters

Button *2

Dual cameras*1

5V USB Type-C interface

3.2 inch TFT screen

8MB SRAM (of which 2MB is used for Al)

Onboard 16MB Flash

Product Size

Module: 25.4*25.4*2. 6mm 

Sheet: 95.8*64*9.8mm

Supply voltage

receive:16mA 

send:0dBm/18mA;10~12dBm/120mA 

Low power consumption:200uA

temperature

4.0-5.2V(typical 5V)@400mA

Operating temperature

-40°C-+85*C


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