EUR 15,00
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: 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. |.
Condizione: New. pp. 210 1st Edition.
EUR 78,05
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 210.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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.
EUR 79,40
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 210.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 112,62
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
EUR 92,27
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
EUR 152,88
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. reprint edition. 210 pages. 9.80x7.10x0.60 inches. In Stock.
EUR 112,77
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. 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 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.
EUR 160,72
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: Like New. Like New. book.
Condizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 331,56
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: New.
Condizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 342,19
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Revaluation Books, Exeter, Regno Unito
EUR 540,16
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 407 pages. 10.25x7.25x0.75 inches. In Stock.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Birkhäuser Boston Sep 2011, 2011
ISBN 10: 1461286468 ISBN 13: 9781461286462
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 139,09
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. 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 geo 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.
Lingua: Inglese
Editore: Birkhäuser Boston, Birkhäuser Boston Sep 2011, 2011
ISBN 10: 1461286468 ISBN 13: 9781461286462
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. 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 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.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 232 pp. Englisch.