Printed and Handwritten Document Analysis
A Machine Learning Perspective
Published on 15. June 2019
Book
Hardback
525 pages
978-1-4822-1962-3 (ISBN)
Description
Presents the fundamentals of machine learning tools and presents their connection to document analysis issues
Familiarizes readers with the graphical model issues in terms of their theoretical background as well as their applicability in document analysis
Addresses circular distributions have potential applications in online handwriting recognition and in color scene text image segmentation
Familiarizes readers with the graphical model issues in terms of their theoretical background as well as their applicability in document analysis
Addresses circular distributions have potential applications in online handwriting recognition and in color scene text image segmentation
More details
Language
English
Place of publication
Oakville
Canada
Target group
College/higher education
Professional and scholarly
Professional Practice & Development
Illustrations
480 s/w Abbildungen
480 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-4822-1962-3 (9781482219623)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Content
Introduction to Machine Learning. Probability Distributions. Graphical Models. Hidden Markov Model. Neural Networks. Kernel Based Methods. Classifier Combination. Introduction to Document Analysis. Sample Databases. Preprocessing. Layout Analysis. Segmentation. Printed and Offline Handwritten Document Recognition. Online Handwriting Recognition. Applications.