KeyLemon and Swissteach demo facial recognition system for student verification

KeyLemon has announced a new partnership with Swisstech AG to introduce facial recognition to Swissteach’s Global Teach online learning management system.

According to the company, the Swissteach/KeyLemon system, which has so far been set up as a demo, supplements legacy username and password logins to guard access to sensitive information using 20 points of facial data. The system also features a one-way verification process that prevents face reconstruction using biometric models.  With the new system, student identities can be checked periodically without any particular interaction from students.

Currently, Swissteach uses hybrid fingerprint-based access control in the production version of its Global Teach learning management system. According to Swissteach, the KeyLemon facial recognition solution shows potential to advance the way users login and interact with learning systems.

“Our face recognition technology is available as an SDK with prebuilt libraries, as well as a cloud-based solution, as illustrated with the demo case,” Gilles Florey, CEO of KeyLemon said. “Rather than spending months recoding, we were able to implement sophisticated face recognition in a matter of days.”

“Controlling access to the system is a big part of the equation,” Heinz Gerber, CEO of Swissteach said. “But we’re also pleased by the language-independent nature of the solution. No matter where users live or how their names appear in various languages, logins are seamless, allowing users to concentrate on learning.”

“We’re very proud of this joint solution,” Reto Schilliger, Product Manager of Global Teach said, “and we’re excited to show our current and potential future customers how it’s poised to take online learning to the next level, as well as serving as a springboard for a limitless number of applications in other industries.”

Reported previously in BiometricUpdate.com, KeyLemon recently launched a new wide-spectrum facial recognition system, developed with SoftKinetic.

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