3D Surface Reconstruction: Multi-Scale Hierarchical Approaches
Autor Francesco Bellocchio, N. Alberto Borghese, Stefano Ferrari, Vincenzo Piurien Limba Engleză Hardback – 29 oct 2012
Innovative approaches, based on two popular machine learning paradigms, namely Radial Basis Functions and the Support Vector Machines, are also introduced. These paradigms are innovatively extended to a multi-scale incremental structure, based on a hierarchical scheme. The resulting approaches allow readers to achieve high accuracy with limited computational complexity, and makes the approaches appropriate for online, real-time operation. Applications can be found in any domain in which regression is required.
3D Surface Reconstruction: Multi-Scale Hierarchical Approaches is designed as a secondary text book or reference for advanced-level students and researchers in computer science. This book also targets practitioners working in computer vision or machine learning related fields.
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 615.03 lei 6-8 săpt. | |
Springer – 9 noi 2014 | 615.03 lei 6-8 săpt. | |
Hardback (1) | 621.04 lei 6-8 săpt. | |
Springer – 29 oct 2012 | 621.04 lei 6-8 săpt. |
Preț: 621.04 lei
Preț vechi: 776.31 lei
-20% Nou
Puncte Express: 932
Preț estimativ în valută:
118.86€ • 125.39$ • 99.05£
118.86€ • 125.39$ • 99.05£
Carte tipărită la comandă
Livrare economică 02-16 ianuarie 25
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9781461456315
ISBN-10: 1461456312
Pagini: 170
Ilustrații: VI, 162 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.42 kg
Ediția:2013
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
ISBN-10: 1461456312
Pagini: 170
Ilustrații: VI, 162 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.42 kg
Ediția:2013
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Introduction.- Scanner systems.- Reconstruction.- Surface fitting as a regression problem.- Hierarchical Radial Basis Functions Networks.- Hierarchical Support Vector Regression.- Conclusion.