Stefano Ferrari – författare

3D Surface Reconstruction: Multi-Scale Hierarchical Approaches presents methods to model 3D objects in an incremental way so as to capture more finer details at each step. The configuration of the model parameters, the rationale and solutions are described and discussed in detail so the reader has a strong understanding of the methodology. Modeling starts from data captured by 3D digitizers and makes the process even more clear and engaging. 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.

3D Surface Reconstruction: Multi-Scale Hierarchical Approaches presents methods to model 3D objects in an incremental way so as to capture more finer details at each step. The configuration of the model parameters, the rationale and solutions are described and discussed in detail so the reader has a strong understanding of the methodology. Modeling starts from data captured by 3D digitizers and makes the process even more clear and engaging. 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.

The aim of this book is to highlight the latest findings in Aniridia research. Aniridia, meaning “without iris”, is a rare genetic disorder affecting vision, characterized by the incomplete formation of the iris (the coloured part of the eye that surrounds the black pupil). It may also cause other segments of the eye to be under-developed such as the optic nerve and the macula (the central part of the retina). Aniridia and associated conditions affect individuals differently. So while some affected people are partially sighted or blind, others may have near normal sight. Aniridia is congenital (present at birth) and is caused by a dysfunction of the PAX6 gene, situated on the 11th chromosome that causes the premature cessation of eye development. Aniridia affects between 1:40,000 to 1:100,000 people, and affects males and females equally. People with Aniridia may also experience secondary conditions such as Photophobia, Nystagmus, Glaucoma, Cataracts and Keratopathy.

The aim of this book is to highlight the latest findings in Aniridia research. Aniridia affects between 1:40,000 to 1:100,000 people, and affects males and females equally.