paper on beef/ultrasound/adaptive logic networks

[Darrell McCauley]

The following paper (11 pages in length) has been placed in the
Neuroprose archive. A shorter version was submitted to Transactions of
the ASAE.  Any comments or questions should be sent to
mccauley at ecn.purdue.edu. This annoucement may be forwarded to other
lists/newsgroups.  Though I cannot mail hardcopies, I may be willing
to e-mail compressed, uuencoded PostScript versions.

Of course, thanks to Jordan Pollack for offering this service.
I find it very valuable.
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          FAT ESTIMATION IN BEEF ULTRASOUND IMAGES USING 
	       TEXTURE AND ADAPTIVE LOGIC NETWORKS 


James Darrell McCauley, USDA Fellow      Brian R. Thane, Graduate Student
 Dept of Agricultural Engineering        Dept of Agricultural Engineering 
        Purdue University                      Texas A&M University
   (mccauley at ecn.purdue.edu)                 (thane at diamond.tamu.edu)
	
	      A. Dale Whittaker, Assistant Professor
                 Dept of Agricultural Engineering
                       Texas A&M University
                      (dale at diamond.tamu.edu)

Overviews of Adaptive Logic Networks and co--occurrence image texture
are presented, along with a brief synopsis of instrument grading of
beef. These tools are used for both prediction and classification of
intramuscular fat in beef from ultrasonic images of both live beef
animals and slaughtered carcasses.  Results showed that Adaptive Logic
Networks perform better than any fat prediction method for beef
ultrasound images to date and are a viable alternative to
statistical techniques.  
\keywords{Meat, Grading, Automation, Ultrasound Images, Neural Networks.}

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filename: mccauley.beef.ps.Z

FTP INSTRUCTIONS

     unix% ftp archive.cis.ohio-state.edu (or 128.146.8.52)
     Name: anonymous
     Password: neuron
     ftp> cd pub/neuroprose
     ftp> binary
     ftp> get mccauley.beef.ps.Z
     ftp> quit
     unix% zcat mccauley.beef.ps.Z | lpr
(or the equivalent)

--
James Darrell McCauley          Department of Ag Engr, Purdue Univ
mccauley at ecn.purdue.edu         West Lafayette, Indiana 47907-1146
** "Do what is important first, then what is urgent." (unknown) **