Robust Computer Vision: Theory and Applications - M. S. Lew,N. Sebe
-30% with code BOOKS
Shipping in 12-18 days
30-day return policy
From the foreword by Thomas Huang: "During the past decade, researchers in computer vision have found that probabilistic machine learning methods are extremely powerful. This book describes some of these methods. In addition to the Maximum Likelihood framework, Bayesian Networks, and Hidden Markov models are also used. Three aspects are stressed: features, similarity metric, and models. Many interesting and ... Full description
You May Also Like
TOP
The Demon-Haunted World: Science as a Candle in the Dark
-30% with code BOOKS
In stock at our supplier
TOP
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
-30% with code BOOKS
Out of stock
TOP
Heart Rate Variability: Science and Strategies for Peak Performance
Marco Altini, Sylvain Laborde, Dan Plews, Emma Mosley
-30% with code BOOKS
Out of stock
TOP
Many Faces, One Purpose: A Manager's Handbook on Women in Firefighting
U. S. Fire Administration, Homeland Security
-30% with code BOOKS
Out of stock
TOP
The Gulf Moment: Arab Relations Since 2011
Florence Gaub, U. S. Army War College, Strategic Studies Institute
-30% with code BOOKS
Out of stock
TOP
Medizinisches Englisch pocket
-30% with code BOOKS
In stock at our supplier
TOP
Introduction to Algorithms
Ronald L. Rivest, Charles E. Leiserson, Clifford Stein, Thomas H. Cormen
-30% with code BOOKS
In stock at our supplier
TOP
Skin in the Game: Hidden Asymmetries in Daily Life
-30% with code BOOKS
Out of stock
TOP
101 Things I Learned in Architecture School
-30% with code BOOKS
In stock at our supplier
TOP
Dinosaurs and Prehistoric Life: The Definitive Visual Guide to Prehistoric Animals
-30% with code BOOKS
In stock at our supplier
TOP
Worth Dying For: The Power and Politics of Flags
-30% with code BOOKS
In stock at our supplier
TOP
Crossing Borders: About the birth of the Consortium of European Research Libraries, the organisation's early years and its path to maturity, spanning the period from the late twentieth century to the first decades of the twenty-first century
-30% with code BOOKS
In stock at our supplier
TOP
The Code Book: The Science of Secrecy from Ancient Egypt to Quantum Cryptography
-30% with code BOOKS
In stock at our supplier
TOP
Playing It by the Book: Printed and Manuscript Book Games in Early Modern Europe
-30% with code BOOKS
In stock at our supplier
TOP
International Economics: Theory and Policy, Global Edition
Paul Krugman, Maurice Obstfeld, Marc Melitz
-30% with code BOOKS
In stock at our supplier
TOP
The Dictionary of Obscure Sorrows
-30% with code BOOKS
In stock at our supplier
TOP
The Unaccountability Machine: Why Big Systems Make Terrible Decisions
-30% with code BOOKS
In stock at our supplier
TOP
Nudge: Improving Decisions About Health, Wealth and Happiness
Cass R Sunstein, Richard H. Thaler
-30% with code BOOKS
In stock
TOP
Einhundert Zitate Female Edition: Ein Postkartenbuch mit 100 Zitaten
-30% with code BOOKS
In stock at our supplier
Description
From the foreword by Thomas Huang: "During the past decade, researchers in computer vision have found that probabilistic machine learning methods are extremely powerful. This book describes some of these methods. In addition to the Maximum Likelihood framework, Bayesian Networks, and Hidden Markov models are also used. Three aspects are stressed: features, similarity metric, and models. Many interesting and important new results, based on research by the authors and their collaborators, are presented. Although this book contains many new results, it is written in a style that suits both experts and novices in computer vision."
More Information
| Author | M. S. Lew, N. Sebe |
|---|---|
| Publisher | Springer Netherlands |
| Series | Computational Imaging and Vision |
| Release year | 2010 |
| Cover type | Softcover |
| EAN | 9789048162901 |