This article will equip you with the knowledge to assess the efficiency requirements of your face recognition system. In turn, you will be able to factor this important consideration into your procurement process and potentially eliminate certain algorithms before the time consuming step of performing internal evaluations.
Perhaps no technology is improving as rapidly as automated face recognition. For example, over the last two years Rank One has reduced the False Non-Match Rate of our algorithm by over 10x: Other face recognition vendors are similarly improving their accuracy at a rapid pace. However, despite these relentless improvements, many vendors are also denying […]
Face recognition technology is rapidly expanding as a convenience technology that allows quick and secure access to sensitive systems and facilities, and for people to ubiquitously interact with their environments. This article highlights the most prominent commercial applications of face recognition technology that are emerging.
Choosing a face recognition algorithm that meets your accuracy requirements can be a daunting process. We simplify this process with a straightforward guide on how to measure algorithm accuracy and determine which algorithms are viable for your application.
Automated face recognition algorithms rely on highly complex mathematical models, but at a high level many of the techniques performed are rather easy to understand. In this article we provide a high level guide of how automated face recognition algorithms work.
A comprehensive set of definitions and terms used when discussing face recognition technology.