Which of the following is a facial feature identification product that can employ artificial intelligence
and can require the system to learn from experience?
A.
All of the choices.
B.
Digital nervous system.
C.
Neural networking
D.
DSV
Explanation:
There are facial feature identification products that are on the market that use other
technologies or methods to capture one’s face. One type of method used is neural
networking technology. This type of technology can employ artificial intelligence that
requires the system to “learn” from experience. This “learning” experience helps the
system to close in on an identification of an individual. Most facial feature
identification systems today only allow for two-dimensional frontal images of one’s
face.
Not DSV:
Signature biometrics are often referred to dynamic signature verification (DSV) and look at the way
we sign our names. [15] The dynamic nature differentiates it from the study of static signatures on
paper. Within DSV a number of characteristics can be extracted from the physical signing process.
Examples of these behavioral characteristics are the angle of the pen is held, the time taken to
sign, velocity and acceleration of the tip of the pen, number of times the pen is lifted from the
paper. Despite the fact that the way we sign is mostly learnt during the years it is very hard to
forge and replicate.