Networks for pattern recognition problems?

[James B Saxon]

In article <23586 at boulder.Colorado.EDU> you write:
>Do you know of any references to work done using connectionist (neural)
>networks for pattern recognition problems? I particularly am interested
>in problems where the network was shown to outperform traditional algorithms.
>
>I am working on a presentation to NOAA (National Oceanic and Atmospheric
>Admin.) management that partially involves pattern recognition
>and am trying to argue against the statement:
>"...results thus far [w/ networks] have not been notably more
>impressive than with more traditional pattern recognition techniques".
>
>I have always felt that pattern recognition is one of the strengths of
>connectionist network approaches over other techniques and would like
>some references to back this up.
>
>thanks much, rich
>========================================================================
>Richard Fozzard					"Serendipity empowers"
>Univ of Colorado/CIRES/NOAA	R/E/FS  325 Broadway, Boulder, CO 80303
>fozzard at boulder.colorado.edu                   (303)497-6011 or 444-3168

 Well, aside from the question of ultimate generality to which the answer 
is "OF COURSE there are references to neural network pattern recognition
systems.  The world is completely full of them!"

Anyway, maybe you'd better do some more research.  Here's a couple off the
top of my head:

Kohonen is really hot in the area, he's been doing it for at least ten
years.  Everybody refers to some aspect of his work.

I also suggest picking up a copy of the IJCNN '90 San Diego, all 18lbs
of it.  (International Joint Conference on Neural Networks) But for a
preview:  I happened to sit in on just the sort of presentation you
would have liked to hear.  His title was "Meterological Classification
of Satellite Imagery Using Neural Network Data Fusion"  Oh Boy!!! Big
title!  Oh, it's by Ira G. Smotroff, Timothy P. Howells, and Steven Lehar.
>From the MITRE Corporation (MITRE-Bedford Neural Network Research Group)
Bedford, MA 01730.  Well the presentation wasn't to hot, he sort of hand
waved over the "classification" of his meterological data though he
didn't describe what we were looking at.  The idea was that the system
was supposed to take heterogeneous sensor data (I hope you know these:
GOES--IR and visual, PROFS database--wind profilers, barometers, solarometers,
thermometers, etc) and combine them.  Cool huh.  If they had actually done
this, I imagine the results would have been pretty good.  It seems though
that they merely used an IR image and a visual image and combined only
these two.  Their pattern recognition involved typical modeling of the
retina which sort of acts as a band pass filter with orientations, thus
it detects edges.  Anyway, their claim was the following:  "The experiments
described showed reasonably good classification performance.  There was no
attempt to determine optimal performance by adding hidden units [Hey, if
it did it without hidden units, it's doing rather well.], altering learning
parameters, etc., because we are currently implementing self-scaling learning
algorithms which will determine many of those issues automatically. [Which
reminds me, Lehar works with Grossberg at Boston University.  He's big
on pattern recognition too, both analog and digital.  Check out Adaptive
Resonance Theory, or ART, ART2, ART3.]..."  Anyway it looks like a 
first shot and they went minimal.  There's lots they could add to
make it work rather well.  In terms of performance, I'd just like to
make one of those comments...  From what I saw at the conference,
neural networks will outperform traditional techniques in this sort of
area.  The conference was brimming over with successful implementations.

Anyway...  Enough rambling, from a guy who should be writing his thesis
right now...  Good luck on your presentation!

Oh, I think it automacally puts my signature on.....

Did it?

-- 
 ---- \ / ----	  /--------------------------------------------\  James Bennett Saxon
|   O|	 |   O|	  |  "I aught to join the club and beat you    |  Visualization Laboratory
|    |   |    |   |   over the head with it." -- Groucho Marx  |  Texas A&M University
 ----     ----   <---------------------------------------------/  jsaxon at cssun.tamu.edu