Empower financial organizations to increase agility and responsiveness, manage complex infrastructures, expand business model boundaries, and deliver customer-centered, superior financial services.
Build a highly available open architecture that flexibly expands system resources based on user demand. Maintain stable response speed during peak events to ensure a seamless user experience and higher satisfaction.
Implement multiple security measures, including identity verification, data encryption, and network isolation, to protect sensitive financial data. Horizontal scaling and load balancing eliminate points of failure and ensure high system availability.
Backward-compatible and adaptable to heterogeneous ICT infrastructure, our solutions provide unified, elastic support to accelerate the migration of traditional applications to modern information and communication technology.
Leverage cloud-native technologies to enable elastic scaling, high availability, and agile deployment. Through containerization, automation, and continuous delivery, financial institutions can innovate faster, reduce costs, and improve operational efficiency.
GPU failures can hinder project progress. Complex system dependencies mean single-node failures may cause system paralysis and potential data loss.
As clusters expand, resource demands diversify, making monitoring, maintenance, and troubleshooting increasingly challenging.
When multiple projects run simultaneously, uneven resource distribution can lead to contention and rising operational costs.
Supports diverse computing devices and schedules resources across thousands of cards. Automatically allocates and manages computing power while refining resource distribution through a unified management platform to maximize utilization efficiency.
Leveraging container technology, clusters are deployed, scaled, and maintained efficiently with consistent environments. Real-time monitoring, visual dashboards, multi-channel alerts, and robust permission management ensure security and resource use.
High-availability architecture and load balancing prevent system-wide failures from single-node issues. AI-driven operation and maintenance monitor faults, automatically isolate problems, migrate tasks, and restart nodes to minimize business disruption.
Researchers can request computing resources independently, while management teams track usage visually. Automated maintenance reduces workload, ensures system stability, and accelerates business iteration and innovation.
The smart campus portrait monitoring system is an integrated face recognition solution combining software and hardware. It features modular functions, unified data management, and a high level of intelligence. With rich capabilities, it meets diverse campus security needs.
Dynamic Facial Capture
Utilizing advanced facial recognition algorithms, the system achieves a capture rate of over 98% and matching accuracy of up to 99.9%, recognizing tens of thousands of faces per second. It automatically selects the most frontal image of each person, while optical flow and detection algorithms enable precise face tracking to avoid duplicate alarms. By deploying cameras at key entrances and exits, complete real-time monitoring of all visitors is ensured.
Performance Indicators:
Capture rate: >98% | False snapshot rate: <2%
1:1 Face Comparison
The 1:1 portrait comparison function determines whether two photos belong to the same individual. It remains highly accurate under various facial expressions (smiling, mouth open, eyes closed), lighting conditions (natural or indoor), head poses (within 20° sideways and 15° up or down), and across age differences, hairstyles, and accessories such as glasses or hats.
Performance Indicators:
For a database of 10,000 people, the false recognition rate is 0.1%, the passing rate reaches 99%, and each comparison takes less than 1 second.
Face 1:N Comparison
The 1:N face comparison identifies a user’s face within a large portrait database, performing dynamic and non-cooperative recognition. Dynamic comparison captures face data from video streams in real time, while non-cooperation allows recognition without requiring the subject to be in a specific location. This process is more challenging than static 1:1 comparison, handling issues like overexposure, backlighting, profile faces, and long-distance recognition.
Performance Indicators:
For a database of 10,000 faces, the false recognition rate is 0.1%, the passing rate reaches 99%, and each comparison takes less than 1 second.
Facial Feature Analysis
This function analyzes key facial attributes such as gender, age, and emotions. Gender and age analysis helps profile the flow of teachers and students on campus, while emotion analysis provides insights into students’ classroom engagement.
Performance Indicators:
Accuracy for gender, age, and emotion analysis exceeds 90% per image.
Supports up to seven types of intelligent terminals, designed for different scenarios to meet diverse facial recognition needs.
The portrait monitoring system offers comprehensive functions that maximize campus security and operational efficiency.
Provides unified management of personnel, equipment, and building data to ensure accuracy and consistency.
Delivers dynamic face capture, feature analysis, and both 1:1 and 1:N comparison for precise identification.
Enable manufacturing enterprises to adopt a data-driven innovation model across production and technology, promoting digital, networked, and intelligent industry transformation.
The unified distributed architecture reorganizes system resources, enabling flexible data, application, and service integration. This accelerates new business responsiveness, drives innovation, supports digital transformation, and enhances user experience.
Comprehensive service capabilities enable equipment interoperability, health management, production traceability, and process optimization, enhancing the overall level of smart manufacturing.
An integrated enterprise big data platform connects the entire production and operation data chain. It simplifies data capture, integration, analysis, and scheduling, improving overall data utilization and application efficiency.
Through open APIs, data can be securely shared, improving industrial chain collaboration and fostering a thriving, interconnected ecosystem.
Leveraging cloud-native technology, we help manufacturing enterprises implement data-driven innovation across production and technology, enabling digital, networked, and intelligent transformation of the industry.
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