Using highly advanced technologies and newest methods,Shenzhen Zento Traffic Equipment Co., Ltd. has developed Time Attendance 5-inch Cylindrical Dynamic Face Automatic Recognition School Community Intelligent Gate Access Control System. It is on sale starting now and we welcome your inquiry. It caters to the foreign markets. In the process of continuous entrepreneurial innovation, Shenzhen Zento Traffic Equipment Co., Ltd. always adhere to the business philosophy of 'quality comes first'. We will grasp the opportunities of the times and always keep up with the industry trends. We believe that one day we will become one of the leading enterprises in the global market.
|Place of Origin:||China||Brand Name:||Zento|
|Model Number:||ZT-F04||Name:||face recognition system|
|Size:||5 inch, 170 degree IPS LCD screen||Equipment dimensions:||560.25*114mm(High * Diameter)|
|Type:||RGB camera, Face||focal length:||6mm|
|Face:||Supporting detection and tracking of 5 people at the same||Deployment mode:||Support the use of public and local area networks|
|Protection Level:||IP66||working temperature:||Negative 20, positive 85|
|Keyword:||facial recognition software;face recognite gate|
Time Attendance Terminal Instrument 5-inch Cylindrical Stainless Steel Face Recognition Machine
Face recognition is a kind of biological recognition technology based on human face feature information. A series of related technologies, which collect the images or video streams containing faces with cameras or cameras, automatically detect and track faces in images, and then recognize the detected faces, which are also called human image recognition and face recognition.
5 inch, 170 degree IPS LCD screen
4 nuclei, 1.8 GHz
1 channel audio output（line out）
Negative 20, positive 85
1. Supporting night light compensation with photosensitive sensor cooperation;
2. Support serial port, Wigan 26, 34 output, output content support configuration;
3. Dynamic face detection and tracking recognition algorithm based on video stream is adopted.
4. Support devices to store 10,000 people's databases locally.
(a) Cloud platform devices support storing 50,000 face photos (less than 4,000 KB), 1 million recognition records (0.45 KB),20,000 live snapshots
(b) LAN devices support storing 20,000 face photos (photos are calculated according to 1,000 KB) and 1 million recognition records (including the most). Nearly 10,000 live snapshots;
5. When the face database is 3000, the recognition accuracy of 1:N is 99.7%.
6. Recognition speed is fast.
(a) Face tracking and detection takes about 20 ms.
(b) Face feature extraction takes about 200 ms.
(c) Face comparison takes about 0.2 Ms. (1000 people database, average recognition takes many times). 0.5 ms. (10000 people database, average recognition takes many times.)
7. Supporting stranger detection and configurable stranger rank;
8. Supporting on-site photo preservation in face recognition or stranger detection;
9. Support HTTP interface docking;
10. Supporting the deployment of public network and local area network;
11. Supporting screen display content configuration;
12. Support Distance Recognition Configuration
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