Face Recognition Access Control Terminal with Digital Detection Module

 Deep learning algorithm model based on UNV independent intellectual property rights, face recognition accuracy rate > 99%, false rate < 1%

 Built-in deep learning dedicated chip, supports local offline recognition, 3,000 face capacity, face whitelist (1∶ N), 10,000 IC card capacity

 Fastest recognition time 0.2 seconds, various model merge mode are used to reduce false rate and increase pass rate

 WDR, 2MP (1080P) low illumination wide-angle camera for capturing high quality image with various complex lighting scenes

 Support anti-spoofing detection based on deep learning algorithm, effective against fraud such as photo and video

 Support face metering and human metering for fast adapting to ambient light

 Suggested height for face recognition: between 0.8m and 2.2m，face recognition distance: 0.2m to 2m

 Support screen sleep mode, keep the minimum brightness to prevent glare at night

 Support add up to 6 photos of the base library for a single person

 Support video capture, support ONVIF protocol

 Support face, card, password authentication to control door open

 Built-in 4G EMMC front end storage, stable and reliable, up to 30,000 events capacity (with images)

 Support direct control door lock, exit button, door contact detection to implement access control management

 Support tamper protection, support door opening timeout, support time exceeding alarm, support keeping door opening while fire alarm active