Graduate Thesis Or Dissertation

 

Selection of discriminating characteristics by partial similarity for the two class recognition problem of artificial intelligence Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/zc77st808

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  • I have developed what I believe to be a very general method of feature extraction. The key to the generality of the method is that we examine each individual characteristic separately with a minimum of dependence upon other characteristics. The basic idea is to discover discriminating characteristics by a linear investigation of each sample in each class of objects being examined for differences. This is facilitated by what I term "partial similarity," that is, we look at only those samples which are partially similar to a base sample with respect to previously discovered discriminating characteristics. The method was investigated by the use of a FORTRAN program using hand printed capital A's and R's as the two classes to discriminate between.
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  • File scanned at 300 ppi (Monochrome) using ScandAll PRO 1.8.1 on a Fi-6770A in PDF format. CVista PdfCompressor 5.0 was used for pdf compression and textual OCR.
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