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To meet demands for efficiency and security, this solution employs deep learning as its core, establishing a ‘front-end capture + back-end processing’ architecture. The front-end utilises high-definition cameras and snapshot devices for real-time facial capture, while the back-end integrates MTCNN detection and ArcFace feature extraction and comparison algorithms. This achieves over 99.8% recognition accuracy with millisecond-level response times.
The solution covers multiple scenarios: access control terminals incorporate liveness detection to prevent fraud, attendance terminals automatically calculate working hours, and surveillance terminals provide real-time alerts for unauthorised individuals. Data transmission and storage employ encryption, complying with the Personal Information Protection Law to safeguard privacy. The system integrates seamlessly with OA and security platforms, reducing costs and enhancing efficiency while balancing security with practicality.
1. Supports rapid facial recognition for personnel identity verification, incorporating liveness detection to prevent photo fraud. Upon successful verification, doors open automatically to enhance access efficiency.
2. Integrates with visitor management systems to register facial data for temporary access authorisation. Unauthorised entry triggers immediate localised audible and visual alarms.

1. Upon employee arrival, cameras automatically recognise facial features, record attendance times, synchronise data to the system, and generate attendance reports automatically.
2. Designed for multi-office scenarios, it supports remote facial recognition clocking for employees across different locations, reducing manual statistical errors and lowering HR attendance management costs.

1. Equipment deployed at school entrances conducts real-time facial recognition of unfamiliar individuals, triggering alerts to security personnel upon detecting anomalies to safeguard student welfare.
2. Integrated with dormitory access control systems, entry is permitted solely to students upon facial verification, preventing unauthorised visitors from entering at will and standardising dormitory management.

1. Upon a member's arrival, the system automatically recognises their facial features, swiftly retrieving their membership details. Staff can then deliver tailored promotional offers with precision.
2. The system records members' visit frequency and spending preferences, providing merchants with user profiling analysis to enhance product and service strategies.

1. Deployed at airport and high-speed rail station security checkpoints, enabling swift facial recognition verification of passenger identity and ticketing details to reduce queuing times.
2. Adapted for metro and bus systems, allowing passengers to complete fare payments and access travel without physical cards via facial recognition, enhancing journey convenience.



400-839-9003
1202, Building B, Nanxian Commercial Plaza, Nanyuan New Village,
Hongshan Community, Minzhi Street, Longhua District, Shenzhen




