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.