BISC Seminar Announcement, April 23rd, 4pm, 310 Soda Hall

Frank Hoffmann (fhoffman@cs.berkeley.edu)
Mon, 20 Apr 1998 21:34:52 +0200 (MET DST)

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B I S C S e m i n a r A n n o u n c e m e n t
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Recognition Technology -- A Technology Whose Time has Come

Lotfi A. Zadeh

Professor in the Graduate School and Director,
Berkeley Initiative in Soft Computing (BISC),
Computer Science Division and the Electronics Research Laboratory,
Department of EECS, University of California, Berkeley, CA 94720-1776
Telephone: 510-642-4959
Fax: 510-642-1712
E-Mail: zadeh@cs.berkeley.edu

Date: Thursday, April 23, 1998
Time: 4-5pm
Location : 310 Soda Hall

Abstract

Recognition systems of one kind or another - among them character
recognition systems, speech recognition systems, handwriting recognition
systems, target recognition systems and pattern recognition systems - have
been around for a long time. But what we are beginning to see today are
recognition systems that are capable of performing tasks that could not be
done in the past. Among examples of such systems are:

1. Computer virus detection system (IBM US Patent 5,675,711).
This system employs a neural network classifier which is trained to detect
both known and new viruses.

2. Eyeprint identification in ATM cash machines. In this system
developed by NCR, a camera captures a digital record of a user's iris and can
verify identity within seconds from a central database.

3. Supermarket checkout scanner (US Patent 5,673,089) which uses scent
sensors to identify fruits and vegetables.

4. Molecular breathanalyzer that can detect diseases such as lung
cancer, stomach ulcer and hepatitis at much earlier stages than currently
used in radiological and laboratory tests.

5. Password authentication using typing biometrics.

6. MailJail software (Omron Advanced System) filters out unwanted
junk e-mail. MailJail is a fuzzy-logic-based rule-based system which
is customizable and is capable of learning user preferences about junk e-mail.

7. Seizure prediction actuator system (Georgia Institute of Technology).
This system can recognize onset of an epileptic fit and can act to prevent it.

The quantum jump in the capabilities of today's recognition systems
reflect three converging developments: (a) major advances in sensor
technology; (b) major advances in sensor data processing technology; and
(c) the use of soft computing techniques to infer a conclusion from
observed data.


Insofar as sensor technology is concerned, the advances in question
relate to both availability and affordability. More specifically, such
sensors as scent sensors, GPS sensors, MEMS sensors and DNA sensors did not
exist in the past. When they did exist, they were unaffordable in terms of
cost, weight, size or reliability. Today, sensor technology, and especially
MEMS technology, provide us with a wide variety of ways in which information
about a process can be obtained and processed at high speed, low cost and
high reliability.

The employment of soft computing - which is a consortium of fuzzy logic,
neurocomputing, evolutionary computing and probabilistic computing - is a
key factor in the enhanced capabilities of recognition systems. To
illustrate, the computer virus recognition system employs neurocomputing
and machine learning; the password authentication system uses fuzzy logic;
the MailJail software is fuzzy logic based; the seizure prediction system
uses a combination of neurocomputing, wavelet analysis and fuzzy logic. In
the future, most advanced recognition systems are likely to employ a
combination of methodologies -rather than a single methodology - drawn from
soft computing.

A basic issue which is central to recognition technology relates to ways
in which sets and, more generally, fuzzy sets can be defined. The
principal modes are: (a) by a listing of elements; (b) by a recognition
algorithm; (c) by a generation algorithm; and (d) by exemplification. An
important part of the recognition process involves methods of passing from
one mode to another. Fuzzy logic plays an essential role in this process.
In the context of recognition, fuzzy logic is closely linked to the
methodology of computing with words (CW).

In coming years, recognition technology is likely to play a pivotal role
in the conception, design, construction and utilization of
information/intelligent systems. After all, recognition is one of the most
basic facets of human reasoning and human cognition.

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Frank Hoffmann UC Berkeley
Computer Science Division Department of EECS
Email: fhoffman@cs.berkeley.edu phone: 1-510-642-8282
URL: http://http.cs.berkeley.edu/~fhoffman fax: 1-510-642-5775
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Frank Hoffmann                               UC Berkeley
Computer Science Division                    Department of EECS
Email: fhoffman@cs.berkeley.edu              phone: 1-510-642-8282
URL: http://http.cs.berkeley.edu/~fhoffman   fax:  1-510-642-5775
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