Recognition of Whiteboard Notes: Online, Offline and Combination
| AUTHOR | Liwicki, Marcus; Liwicki, Marcus; Bunke, Horst |
| PUBLISHER | World Scientific Publishing Company (08/01/2008) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Commercial recognition systems are included in a multiple classifier system. The experimental results on the test set show a highly significant improvement of the recognition performance to more than 86%.
Show More
Product Format
Product Details
ISBN-13:
9789812814531
ISBN-10:
9812814531
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
228
Carton Quantity:
40
Product Dimensions:
6.00 x 0.70 x 9.00 inches
Weight:
1.35 pound(s)
Feature Codes:
Bibliography,
Index,
Table of Contents,
Illustrated
Country of Origin:
SG
Subject Information
BISAC Categories
Computers | Computer Science
Computers | Artificial Intelligence - Computer Vision & Pattern Recognit
Dewey Decimal:
006.42
Library of Congress Control Number:
2009275511
Descriptions, Reviews, Etc.
publisher marketing
This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Commercial recognition systems are included in a multiple classifier system. The experimental results on the test set show a highly significant improvement of the recognition performance to more than 86%.
Show More
List Price $128.00
Your Price
$126.72