Learning geometry computational approaches (12 risultati)
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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Da: La bataille des livres, Pradinas, FranciaLa bataille des livres
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Condizione: Très bon. Learning and Geometry: Computational Approaches | Kueker, Smith | Birhaüser, 1996. In-8° cartonné, 210 pages. Couverture propre. Dos solide. Intérieur frais sans soulignage ou annotation. Exemplaire de bibliothèque : petit code barre en pied de 1re de couv., cotation au dos, rares et discrets petits tampons… à l'intérieur de l'ouvrage. Très bon état général pour cet ouvrage. [Ba 46+] Pour les expéditions internationales, nous consulter au préalable pour l ajustement des frais de port qui seront peut-être revus à la baisse/ For international shipments, please contact us in advance to adjust shipping costs. |.
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Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.Romtrade Corp.
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Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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EUR 92,18
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: moluna, Greven, Germaniamoluna
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EUR 92,27
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Condizione: New.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 155,47
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Paperback. Condizione: Brand New. reprint edition. 210 pages. 9.80x7.10x0.60 inches. In Stock.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 112,77
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The field of computational learning theory arose out of the desire to for mally understand the process of learning. As potential applications to artificial intelligence became apparent, the new field grew rapidly. The learning of geo metric object…s became a natural area of study. The possibility of using learning techniques to compensate for unsolvability provided an attraction for individ uals with an immediate need to solve such difficult problems. Researchers at the Center for Night Vision were interested in solving the problem of interpreting data produced by a variety of sensors. Current vision techniques, which have a strong geometric component, can be used to extract features. However, these techniques fall short of useful recognition of the sensed objects. One potential solution is to incorporate learning techniques into the geometric manipulation of sensor data. As a first step toward realizing such a solution, the Systems Research Center at the University of Maryland, in conjunction with the Center for Night Vision, hosted a Workshop on Learning and Geometry in January of 1991. Scholars in both fields came together to learn about each others' field and to look for common ground, with the ultimate goal of providing a new model of learning from geometrical examples that would be useful in computer vision. The papers in the volume are a partial record of that meeting.
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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Hardcover. Condizione: Like New. Like New. book.
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 139,09
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The field of computational learning theory arose out of the desire to for mally understand the process of learning. As potential applications to artificial intelligence became apparent, the new field grew rapidly. The learning of g…eo metric objects became a natural area of study. The possibility of using learning techniques to compensate for unsolvability provided an attraction for individ uals with an immediate need to solve such difficult problems. Researchers at the Center for Night Vision were interested in solving the problem of interpreting data produced by a variety of sensors. Current vision techniques, which have a strong geometric component, can be used to extract features. However, these techniques fall short of useful recognition of the sensed objects. One potential solution is to incorporate learning techniques into the geometric manipulation of sensor data. As a first step toward realizing such a solution, the Systems Research Center at the University of Maryland, in conjunction with the Center for Night Vision, hosted a Workshop on Learning and Geometry in January of 1991. Scholars in both fields came together to learn about each others' field and to look for common ground, with the ultimate goal of providing a new model of learning from geometrical examples that would be useful in computer vision. The papers in the volume are a partial record of that meeting. 232 pp. Englisch.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 106,99
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The field of computational learning theory arose out of the desire to for mally understand the process of learning. As potential applications to artificial intelligence became apparent, the new field grew rapidly. The learning of geo m…etric objects became a natural area of study. The possibility of using learning techniques to compensate for unsolvability provided an attraction for individ uals with an immediate need to solve such difficult problems. Researchers at the Center for Night Vision were interested in solving the problem of interpreting data produced by a variety of sensors. Current vision techniques, which have a strong geometric component, can be used to extract features. However, these techniques fall short of useful recognition of the sensed objects. One potential solution is to incorporate learning techniques into the geometric manipulation of sensor data. As a first step toward realizing such a solution, the Systems Research Center at the University of Maryland, in conjunction with the Center for Night Vision, hosted a Workshop on Learning and Geometry in January of 1991. Scholars in both fields came together to learn about each others' field and to look for common ground, with the ultimate goal of providing a new model of learning from geometrical examples that would be useful in computer vision. The papers in the volume are a partial record of that meeting.Springer Nature c/o IBS, Benzstrasse 21, 48619 Heek 232 pp. Englisch.
