Verwandte Artikel zu Topological Vector Spaces 2
Inhaltsangabe
During the last twenty years the problem of pattern recognition (specifically, image recognition) has been studied intensively by many investigators, yet it is far from being solved. The number of publications increases yearly, but all the experimental results-with the possible exception of some dealing with recognition of printed characters-report a probability of error significantly higher than that reported for the same images by humans. It is widely agreed that ideally the recognition problem could be thought of as a problem in testing statistical hypotheses. However, in most applications the immediate use of even the simplest statistical device runs head on into grave computational difficulties, which cannot be eliminated by recourse to general theory. We must accept the fact that it is impossible to build a universal machine which can learn an arbitrary classification of multidimensional signals. Therefore the solution of the recognition problem must be based on a priori postulates (concerning the sets of signals to be recognized) that will narrow the set of possible classifications, i.e., the set of decision functions. This notion can be taken as the methodological basis for the approach adopted in this book.
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Reseña del editor
During the last twenty years the problem of pattern recognition (specifically, image recognition) has been studied intensively by many investigators, yet it is far from being solved. The number of publications increases yearly, but all the experimental results-with the possible exception of some dealing with recognition of printed characters-report a probability of error significantly higher than that reported for the same images by humans. It is widely agreed that ideally the recognition problem could be thought of as a problem in testing statistical hypotheses. However, in most applications the immediate use of even the simplest statistical device runs head on into grave computational difficulties, which cannot be eliminated by recourse to general theory. We must accept the fact that it is impossible to build a universal machine which can learn an arbitrary classification of multidimensional signals. Therefore the solution of the recognition problem must be based on a priori postulates (concerning the sets of signals to be recognized) that will narrow the set of possible classifications, i.e., the set of decision functions. This notion can be taken as the methodological basis for the approach adopted in this book.
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Image Pattern Recognition
Verlag:
Springer Verlag, 1980
ISBN 10: 0387904409
ISBN 13: 9780387904405
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Anbieter: Munster & Company LLC, ABAA/ILAB, Corvallis, OR, USA
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Zustand: Good. Springer Verlag, 1980. This Book is in Good Condition; First printing with full number line. Normal wear to covers and edges, previous owner's bookplate on front pastedown, text is clean with no marks, binding tight. Not Ex-Library or Remaindered. 100% Guaranteed. hardcover. Good. Bestandsnummer des Verkäufers 621990
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Image Pattern Recognition
Verlag:
Springer Verlag 1980, 1980
ISBN 10: 0387904409
ISBN 13: 9780387904405
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Hardcover
Erstausgabe
Anbieter: Tacoma Book Center, Tacoma, WA, USA
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ISBN 0-387-90440-9. Hardback. No Dustjacket. First Printing. Light edgewear, previous owner's name on front free endpaper, otherwise a Tight sound unmarked copy in Very Good condition. Bestandsnummer des Verkäufers 95040
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TOPOLOGICAL VECTOR SPACES II
Verlag:
Springer-Verlag, New York, 1979
ISBN 10: 0387904409
ISBN 13: 9780387904405
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Hardcover
Erstausgabe
Anbieter: J. Wyatt Books, Ottawa, ON, Kanada
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Hardcover. Zustand: Near Fine. First Edition. 331 pages in excellent condition. Yellow cloth, black titles. Light fading on the spine and edges. Corners not bumped. Scarce. NEAR FINE. Book. Bestandsnummer des Verkäufers 210882
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