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From: mek4_ltd@uhura.cc.rochester.edu (Mark Kern)
Newsgroups: comp.ai.neural-nets
Subject: Re: Networks for pattern recognition problems?
Message-ID: <8462@ur-cc.UUCP>
Date: 18 Jul 90 19:00:40 GMT
References: <23586@boulder.Colorado.EDU> <5856@jhunix.HCF.JHU.EDU>
Reply-To: mek4_ltd@uhura.cc.rochester.edu (Mark Kern)
Organization: University of Rochester
Lines: 32

In article <5856@jhunix.HCF.JHU.EDU> ins_atge@jhunix.UUCP (Thomas G Edwards) writes:
>In article <23586@boulder.Colorado.EDU> fozzard@boulder.Colorado.EDU (Richard Fozzard) writes:
>>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".
>
>That's a difficult statement to argue against.  I do not recall any
>neural network techniques for pattern recognition which _perform_
>notably better than traditional pattern recognition techniques.
>

	I hope I did not take the quote too far out of context. I'm not
sure what the underscores around the "perform" mean.  I have often
wondered about neural-net performance over traditional pattern
classification techniques.  I seem to recall though, that neural-nets are
demonstratably better at recognizing cursive handwriting.  Can anyone
verify or refute this? If performance is supposed to mean "speed", then
one can argue that we don't have many neural-nets running in true
parallel yet to make a comparison.  I personally find it hard to believe
that traditional methods would be faster for something such as vision
processing, but I am not very familiar with neural nets.

Mark Kern


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