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Amazon Rekognition

Enhance the precision of Amazon Rekognition Face Search by utilizing user vectors.

In numerous industries such as finance, telecommunications, and healthcare, online identity verification is a critical process. This is often done using a multi-step digital identity process, one example of which is face search, which matches an end-user's face with those in an existing account. A variety of steps are necessary to build an accurate face…

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Construct a dynamic learning pipeline for auto-labelling of photos using AWS services.

Veoneer, a global leader in automotive electronic safety systems, collaborated with Amazon to develop an active learning pipeline for in-cabin sensing. Collaborating with Amazon's Worldwide Specialist Organization and the Generative AI Innovation Centre, they were able to cut costs by 90% and speed up the annotation process from weeks to hours. In-cabin sensing uses cameras, radar,…

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Enhancing Content Moderation using Amazon Rekognition’s Mass Analysis and Personalized Moderation

Amazon Rekognition is designed to easily incorporate image and video analysis into applications, all backed by the robust deep learning technology engine developed by Amazon. The technology does not require machine learning expertise for usage and continuously boosts its system with fresh computer vision features. Amazon Rekognition presents a user-friendly API which can rapidly assess…

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