Now Available: ROC SDK version 1.20, featuring substantial accuracy improvements and a more robust API
Rank One announces a major enhancement to the ROC face recognition SDK with the newly released version 1.20. The most significant improvement is in face recognition accuracy, with as much as a 40% reduction in error rates. The embedded algorithm algorithm that ships...
Overview of ROC SDK Version 1.20
The ROC SDK version 1.20 delivers major accuracy improvements, alongside a wide range of other algorithmic and functionality enhancement.
Facial Recognition Code of Ethics
Rank One Computing believes in a just, non-violent world of equality and fairness. We prize democratic values, civil liberties and open and informed debate. When used to further these values, automated face recognition can continue to make the world a safer, better place for everyone. In the absence of regulatory guidance, we wish to advance limitations that we believe are appropriate in how face recognition should be utilized.
The following set of ethics serve as a guideline for how we will develop face recognition systems and how we will expect our integration partners and end-users to develop and utilize face recognition systems based on our algorithms
Rank One joins ITIF’s “Open Letter to Congress on Facial Recognition”
Rank One Computing joined prominent research organizations, law enforcement groups, and technology companies last week in sending an open letter to Congress that clarifies the misinformation being circulated regarding the technology, and pledges to support properly...
Race and Face Recognition Accuracy: Common Misconceptions
There is a misperception that face recognition algorithms do not work on persons of color, or are otherwise inaccurate in general. This is not true. The truth is that across a wide range of applications, modern face recognition algorithms achieve remarkably high accuracy on all races, and accuracy continues to improve at an exponential rate.
Rank One achieves top matching algorithm performance in DHS Biometric Technology Rally
Rank One’s industry-leading facial recognition matching algorithm achieved the highest overall accuracy at the Department of Homeland Security’s second annual Biometric Technology Rally. The 2019 DHS Rally benchmarked automated airport security solutions by testing...
Hardware requirements for video processing applications – Part 1: Template generation
When automated face recognition technology is used for analyzing streaming video, an important question is: how much computer hardware is needed? The hardware required to process video depends on several factors which will be discussed in this article.
Hardware requirements for video processing applications – Part 2: Template comparison
In this article we explain how to factor in the computational demand for template comparison in video processing applications. While this task is not as computational burdensome as template generation, for larger-scale applications it can become meaningful.
Now Available: ROC SDK version 1.19, featuring substantial accuracy improvements and several new features
Rank One Computing has released version 1.19 of the ROC SDK, its flagship facial recognition solution, featuring accuracy improvements across all use cases and important new features. Improved Facial Recognition Accuracy - Version 1.19 delivers across-the-board...
Overview of ROC SDK Version 1.19
The ROC SDK version 1.19 delivers top-tier accuracy and industry leading efficiency. This new version comes with accuracy improvements, clustering enhancements, homomorphic encrypted matching, GPU enrollment, and several other enhancements.