Learning and Geometry: Computational Approaches: Computational Approaches (Progress in Computer Science and Applied Logic (PCS)) - Softcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
Other Popular Editions of the Same Title
Search results for Learning and Geometry: Computational Approaches: Computation...
Stock Image
Learning and Geometry: Computational Approaches (eng)
Print on DemandSeller: Brook Bookstore On Demand, Napoli, NA, Italy
Seller rating 4 out of 5 stars
Condition: new. Questo è un articolo print on demand. Seller Inventory # 4QXJMZ887A
Buy New
US$ 101.83
US$ 6.31 shipping
Ships from Italy to U.S.A.
Ships from Italy to U.S.A.
Quantity: Over 20 available
Seller Image
Learning and Geometry: Computational Approaches
Seller: moluna, Greven, Germany
Seller rating 4 out of 5 stars
Condition: New. Seller Inventory # 4191207
Buy New
US$ 108.95
US$ 56.16 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: Over 20 available
Stock Image
Learning and Geometry: Computational Approaches
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Brand New. reprint edition. 210 pages. 9.80x7.10x0.60 inches. In Stock. Seller Inventory # x-1461286468
Buy New
US$ 176.10
US$ 13.26 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 2 available
Seller Image
Learning and Geometry: Computational Approaches
Published by
Birkhäuser Boston Sep 2011, 2011
ISBN 10: 1461286468
ISBN 13: 9781461286462
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9781461286462
Buy New
US$ 164.23
US$ 26.37 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 2 available
Seller Image
Learning and Geometry: Computational Approaches
Seller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Learning and Geometry: Computational Approaches | David Kueker (u. a.) | Taschenbuch | Progress in Computer Science and Applied Logic | xiv | Englisch | 2011 | Birkhäuser | EAN 9781461286462 | Verantwortliche Person für die EU: Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 106372191
Buy New
US$ 113.00
US$ 80.25 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 5 available
Seller Image
Learning and Geometry: Computational Approaches
Published by
Birkhäuser Boston, Birkhäuser Boston Sep 2011, 2011
ISBN 10: 1461286468
ISBN 13: 9781461286462
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9781461286462
Buy New
US$ 126.33
US$ 68.78 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available
Seller Image
Learning and Geometry: Computational Approaches
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9781461286462
Buy New
US$ 133.15
US$ 71.34 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available