Learn some basic of pattern recognition.ppt

pattern recognition

1. A PRESENTATION ON:
PATTERN
RECOGNITION
SATOSI WATANABE’S INTERPRETATION OF PATTERN RECOGNITION: HUMAN AND MECHANICAL
DANA VIGRAN

2. WHAT IS A PATTERN?
•Watanabe describes a pattern as the opposite of chaos
•An entity
•Anything that could be given a name or a specific description
•Any image that we recognize is a pattern

3. HOW MANY PATTERNS CAN YOU
SEE AT ONE TIME?
•Two or more patterns can exist within on image or thing
•Humans can only actively see one pattern at a time
•Examples of this are visual illusions

4. WHAT DO YOU SEE?

5. AGAIN, WHAT DO YOU SEE?

6. CLASSES
•The Human brain separates things out into classes or families
•These categories are the way that we learn
•Dog example: If a child has never seen an animal before, and the mother
shows her child three or four dogs, the child can then look at any animal and
say whether or not it is a dog.

7. PARADIGM ORIENTED PATTERN
RECOGNITION
•In the case of pattern recognition, a paradigm=an individual
object standing for a class
•Each paradigm has a “domain of similarity” that determines
what does or does not belong to the same class as the
paradigm.
•There are two extreme examples of what a paradigm’s
“domain of similarity” might look like

8. DOMAIN OF SIMILARITY
•Example #1: In the most
simplistic scenario, a
paradigm’s domain of
similarity would
encompass everything in
it’s class.

9. DOMAIN OF SIMILARITY CONT.
•Example #2: In the most
complex scenario, each
paradigm’s domain of
similarity would only
encompass one other
example from it’s class,
so effectively, the
paradigm’s would be
linked.

10. STAGES OF PARADIGM
ORIENTED PATTERN
RECOGNITION
•There are two main stages of paradigm oriented
pattern recognition.
•Stage #1: the “tutorial stage” or “learning stage”
during which the machine (or human) is shown
paradigms and has to determine the class domain
•Stage #2: the “application stage” or “decision stage” in
which the machine is shown a newcomer whose class
belonging is not known and has to make the decision
as to the class affiliation.

11. IVAN PETROVICH PAVLOV
•Ivan Petrovich Pavlov
(1849-1936) was a
scientist whose study of
the digestive system led
him to study reflexes as
well
•Famous example of
Pavlov’s dog

12. PAVLOVIAN GENERALIZATION
•Further studies were done in the style of Pavlov’s dog, and
as long as stimulus S was given, the reaction R would be
the same
•Then, if a stimulus similar to S, S` was given instead, R
would be the same
•This shows a different type of pattern recognition: the
similarity between S and S` was recognized and generalized
so that the same output, R, was given

13. HUMAN VS. MECHANICAL
•Current study in pattern recognition focuses on human cognitive capabilities
•A general interest in a more detailed and intricate knowledge of the brain

14. MECHANICAL USES
•Current mechanical applications are a little bit mundane
•Examples:
•Vocal recognition programs
•Text sorting (spam in email etc…)
Recognition of faces that we talked about in class.

15. IS EVERYTHING PATTERN
RECOGNITION?
•Watanabe argues that pattern recognition is the basic
foundation for the working of the brain
•Pattern recognition can be applied to abstract concepts as
well as concrete categories
•After stating these points, Watanabe says “Therefore, we
cannot condemn some of the enthusiastic experts of pattern
recognition claiming that all intellectual acts are pattern
recognition.”

16. THE FUTURE OF PATTERN
RECOGNITION…
•Computer’s have efficiently mastered some forms of pattern recognition
•If all intellectual activity is made up of pattern recognition, might further
development of pattern recognition be another route to artificial
intelligence?