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Foundations of multidimensional and metric data structures

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  • 1024 strony
  • 36 godzin czytania

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Foundations of Multidimensional and Metric Data Structures provides a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions. The book is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.

Zakup książki

Foundations of multidimensional and metric data structures, Hanan Samet

Język
Rok wydania
2006
Oprawa
(twarda)
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Tytuł
Foundations of multidimensional and metric data structures
Język
angielski
Rok wydania
2006
Oprawa
twarda
Liczba stron
1024
ISBN10
0123694469
ISBN13
9780123694461
Seria
Ocena
4,5 z 5
Opis
Foundations of Multidimensional and Metric Data Structures provides a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions. The book is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.