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  6. [FaceMe Case Study] Managing attendance and absence with smartphones and tablets.

[FaceMe Case Study] Managing attendance and absence with smartphones and tablets.

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last updated:Jul 30, 2025

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Introducing a case where a cloud-based human resource management system integrates a facial recognition system, enabling attendance and absence management via smartphones and tablets.

Logsafe, a human resource management solution provider in India, has integrated FaceMe's fast and highly accurate facial recognition engine with anti-spoofing features into its attendance management app, serving over 30,000 customers across various industries in India. **Strengths of FaceMe** - **High-precision facial recognition engine**: Achieved a high authentication rate of up to 99.83% in benchmark tests conducted by the National Institute of Standards and Technology (NIST). - **World-class anti-spoofing technology**: FaceMe's anti-spoofing technology has received iBeta PAD Level 2 certification and ranked first in the PAD tests conducted by the National Institute of Standards and Technology (NIST). - **High versatility**: Can be implemented on various devices such as workstations, PCs, mobile devices, access control devices, POS systems, and kiosks. It is highly accurate and versatile, supporting many operating systems and platforms, including Android and iOS. *For more details, please refer to the PDF document or feel free to contact us.*

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[FaceMe Case Study] Managing attendance and absence with smartphones and tablets.

スクリーンショット 2024-05-28 181527.png
スクリーンショット 2024-05-28 181527.png
  • Related Link - https://jp.cyberlink.com/faceme/insights/cases/sec…

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**Background of Introduction** Logsafe, a human resource management solution provider in India, offers a cloud-based application that allows users to manage clocking in and out as well as attendance using smartphones and tablets. To enhance identity verification and prevent fraudulent clocking, they sought integration with facial recognition technology that meets the following criteria: ■ Support for iOS and Android A facial recognition engine that can operate on iOS and Android is required for integration into Logsafe's cloud attendance management application. ■ Offline Authentication They desire smooth usage that is unaffected by network interruptions during facial recognition. ■ Fraud Prevention Features To prevent fraudulent clocking using images or videos, impersonation prevention features are necessary. *For more details, please refer to the PDF document or feel free to contact us.*

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[FaceMe Case Study] Integration into a cloud-based human resource management system, enabling attendance management through facial recognition via a mobile app.

[FaceMe Case Study] Integration into a cloud-based human resource management system, enabling attendance management through facial recognition via a mobile app.

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Founded in 1996, we are a global leader in AI facial recognition technology based in Taiwan. We offer AI facial recognition solutions such as FaceMe SDK, FaceMe Security, and FaceMe Platform. FaceMe SDK is a proven AI facial recognition engine adopted by various products and services. It has received very high evaluations from third-party organizations such as NIST and offers a variety of features, including anti-spoofing capabilities. FaceMe Security is a proven smart security system used in office buildings, commercial facilities, and factories. It also supports integration with external services and door access control. FaceMe Platform allows the FaceMe AI facial recognition engine to be deployed across various platforms via a Web API. This enables rapid development and evaluation, allowing for efficient development that is not constrained by programming languages. Please feel free to contact us if you have any inquiries. https://jp.cyberlink.com/faceme/

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