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300ms 92% Face Recognition Temperature Measurement Thermal Camera

Shenzhen Kadymay Technology Co., Ltd.
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300ms 92% Face Recognition Temperature Measurement Thermal Camera

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Brand Name : Kadymay

Model Number : KDM-FT8203EW

Certification : CE FCC

Place of Origin : China

MOQ : 50pcs

Price : USD648/pcs, Negotiated

Payment Terms : L/C, D/A, D/P, T/T, Western Union, MoneyGram

Supply Ability : 200per week

Delivery Time : 5-16

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Fever screening thermographic terminal
Temperature Measurement Face Recognition Algorithms Camera Thermal Camera SIlver Color

Introduction

Based on AR9201 AI chip, with the support of powerful computing power and face recognition algorithms, Our Fever Screening Thermographic Terminals are designed to detect elevated skin-surface temperatures, and can thus be used for rapid and preliminary fever screening in office buildings;new face recognition system for identify people wearing masks, granting access only to verified personnel and eliminating possible fraudulent activities.


Highlights

  • AI detection to reduce false alarms from other heat sources meet medical grade accuracy ±0.3 ℃
  • 300ms temperature detection for one person
  • New face recognition system for identify people wearing masks

Features
/ High sensitivity thermal module
l Measure forehead area only with AI face recognition algorithms
l Vanadium Oxide Uncooled Focal Plane Arrays
l 120*90 high resolution in thermal channel
l Temperature Distance: 0.3-1.5m
l Temperature Accuracy:±0.3 ℃
l Reliable fever detection alarm

/ Support face recognition with respirator

l Face recognize without removing their respirator
l Forehead temperature measurement within 100ms
l Recognition accuracy> 92%
l Real-time temperature abnormal alarm

/ Various door opening methods

l Multiple verfication methods: faces, cards and more
l RS485,TCP/IP interface

Specifications

Specifications KDM-FT8203EW
Thermal Module
Image Sensor Vanadium Oxide Uncooled Focal Plane Arrays
Thermal Iaging Pxels 10000
Infrared Rsolution 120*90@15fps
Temperature Distance 0.3-1.5m
Temperature Accuracy ±0.3 ℃
Hardware
processor AR9201
operating system Linux
storage 8GB EMMC+1G DDR4
LCD 7 inches, 1024 * 600 resolution
Optical Module
Image Sensor 2 million effective pixels, 1920 * 1080 SONY IMX
Signal to noise ratio ≥50db(AGC OFF)
Wide dynamic range ≥120dB
Camera Dual cameras, 650nm and 850nm NIR

Face recognition
performance

Face Spoofing

Support Face Spoofing Detection Using Active
Near-Infrared Videos

Verfication height 1.2 ~ 2.2 meters, adjustable angle
Faces capacity 30000
Verfication distance 0.3 ~ 2 meters, variable depending on the lens
Face angle 30 degrees left and right, 30 degrees up and down
Interface
Alarm input 2 alarm inputs
Alarm Output 1 alarm output
power supply DV12V
Network Interface 1 RJ45 10M / 100M Ethernet port
1 *2.4G wifi module (optional)
1 *4G module (optional)
usb interface 1 USB 2.0 interface
Wiegand interface 1 pair Wiegand interface
Machine parameters
Operating temperature Operating temperature: -40 ° c ~ + 60 ° c
Power Maximum power <24w, 12v power supply
Dimensions 120mm*226.5mm*33.5mm



Algorithm parameters

Scenes

Supported
algorithms

Description
Algorithm accuracy

Face recognition (1: 1):
99%@0.01% (accuracy rate is 99% under 0.01% false rate)
95%@0.0001% (95% accuracy under 0.0001% false
positive rate)

Angle requirementsYaw ± 30 degrees, roll ± 30 degrees, pitch ± 15 degrees
Face requirementsFace size is more than 80 * 80 pixels in images



Face live detection

Angle requirementsYaw ± 30 degrees, roll ± 30 degrees, pitch ± 15 degrees
Face requirementsFace size is more than 80 * 80 pixels in images
Algorithm accuracy

98%@0.01% (real person pass rate @false person pass
rate)

Non-living categoryNon-living detection for pictures, videos, coated paper, face fake models, etc.


Face detection and tracking

SnapshotsMore than 30 people / frame
Snapshot frame rate25fps
Smallest face30*30
Adaptation angleYaw ± 45 degrees, roll ± 45 degrees, pitch ± 30 degrees
Attribute contentGender, age, glasses, expression (angry, calm, happy, sad,


Face attribute recognition

surprised), mask, race, beard, race, hat detection, hard hat
detection





Algorithm accuracy

Age accuracy (± 5 years): more than 85%; Gender accuracy: 96% or more;
Skin tone accuracy: above 97%; Beard accuracy: above 97%; Glasses accuracy: more than 98%; Mask accuracy: more than 98%; Hat accuracy: above 97%;
Expression accuracy: 88% or more
















































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