MARC details
000 -LEADER |
fixed length control field |
04158nam a22004815i 4500 |
001 - CONTROL NUMBER |
control field |
978-3-540-76280-5 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20170628034811.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
100301s2008 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783540762805 |
-- |
978-3-540-76280-5 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-3-540-76280-5 |
Source of number or code |
doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA329-348 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA640-643 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
TBJ |
Source |
bicssc |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
MAT003000 |
Source |
bisacsh |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
519 |
Edition number |
23 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Marinai, Simone. |
Relator term |
editor. |
245 10 - TITLE STATEMENT |
Title |
Machine Learning in Document Analysis and Recognition |
Medium |
[electronic resource] / |
Statement of responsibility, etc |
edited by Simone Marinai, Hiromichi Fujisawa. |
264 #1 - |
-- |
Berlin, Heidelberg : |
-- |
Springer Berlin Heidelberg, |
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2008. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
XII, 434 p. 142 illus. |
Other physical details |
online resource. |
336 ## - |
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text |
-- |
txt |
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rdacontent |
337 ## - |
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computer |
-- |
c |
-- |
rdamedia |
338 ## - |
-- |
online resource |
-- |
cr |
-- |
rdacarrier |
347 ## - |
-- |
text file |
-- |
PDF |
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rda |
490 1# - SERIES STATEMENT |
Series statement |
Studies in Computational Intelligence, |
International Standard Serial Number |
1860-949X ; |
Volume number/sequential designation |
90 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
to Document Analysis and Recognition -- Structure Extraction in Printed Documents Using Neural Approaches -- Machine Learning for Reading Order Detection in Document Image Understanding -- Decision-Based Specification and Comparison of Table Recognition Algorithms -- Machine Learning for Digital Document Processing: from Layout Analysis to Metadata Extraction -- Classification and Learning Methods for Character Recognition: Advances and Remaining Problems -- Combining Classifiers with Informational Confidence -- Self-Organizing Maps for Clustering in Document Image Analysis -- Adaptive and Interactive Approaches to Document Analysis -- Cursive Character Segmentation Using Neural Network Techniques -- Multiple Hypotheses Document Analysis -- Learning Matching Score Dependencies for Classifier Combination -- Perturbation Models for Generating Synthetic Training Data in Handwriting Recognition -- Review of Classifier Combination Methods -- Machine Learning for Signature Verification -- Off-line Writer Identification and Verification Using Gaussian Mixture Models. |
520 ## - SUMMARY, ETC. |
Summary, etc |
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi?ers. However, developing a DAR system is a complex engineering task that involves the integration of multiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted to character recognition and word recognition, other tasks such as pre-processing, layout analysis, character segmentation, and signature veri?cation have also bene?ted much from machine learning algorithms. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering mathematics. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Appl.Mathematics/Computational Methods of Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Fujisawa, Hiromichi. |
Relator term |
editor. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9783540762799 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
Uniform title |
Studies in Computational Intelligence, |
-- |
1860-949X ; |
Volume number/sequential designation |
90 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-3-540-76280-5">http://dx.doi.org/10.1007/978-3-540-76280-5</a> |
912 ## - |
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ZDB-2-ENG |