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BISC The Electrical
Engineering and Computer Sciences Department |
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BISC
SIG in Recognition Technology Major
advances in sensor-related technology in combination with soft computing and
machine learning techniques are providing many new tools which make it
possible to conceive design and construct recognition systems which are
capable of performing tasks that could not be performed in the past.
Recognition Technology lies at the center of information/intelligent Systems
and is quintessential in the automation of decision processes. Recognition Technology -- A Technology Whose Time has Come.
Lotfi A. Zadeh 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. Optimized for Web browsers Version 5+. |
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Fuzzy Set: 1965 … Fuzzy Logic: 1973 … BISC: 1990 …
Human-Machine Perception: 2000 - … |
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