MARC details
| 000 -LEADER |
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| fixed length control field |
03199nam a22004455i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
978-3-642-24797-2 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20170628035613.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
120205s2012 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783642247972 |
| -- |
978-3-642-24797-2 |
| 024 7# - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
10.1007/978-3-642-24797-2 |
| Source of number or code |
doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
Q342 |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
UYQ |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
COM004000 |
| Source |
bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.3 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Graves, Alex. |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
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| Title |
Supervised Sequence Labelling with Recurrent Neural Networks |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc |
by Alex Graves. |
| 264 #1 - |
|---|
| -- |
Berlin, Heidelberg : |
| -- |
Springer Berlin Heidelberg, |
| -- |
2012. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
XIV, 146 p. |
| Other physical details |
online resource. |
| 336 ## - |
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| -- |
text |
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txt |
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rdacontent |
| 337 ## - |
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| -- |
computer |
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c |
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rdamedia |
| 338 ## - |
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| -- |
online resource |
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cr |
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rdacarrier |
| 347 ## - |
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| -- |
text file |
| -- |
PDF |
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rda |
| 490 1# - SERIES STATEMENT |
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| Series statement |
Studies in Computational Intelligence, |
| International Standard Serial Number |
1860-949X ; |
| Volume number/sequential designation |
385 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Introduction -- Supervised Sequence Labelling -- Neural Networks -- Long Short-Term Memory -- A Comparison of Network Architectures -- Hidden Markov Model Hybrids -- Connectionist Temporal Classification -- Multidimensional Networks -- Hierarchical Subsampling Networks. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary. The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional recurrent neural networks extend the framework in a natural way to data with more than one spatio-temporal dimension, such as images and videos. Thirdly, the use of hierarchical subsampling makes it feasible to apply the framework to very large or high resolution sequences, such as raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| 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 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
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| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9783642247965 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Studies in Computational Intelligence, |
| -- |
1860-949X ; |
| Volume number/sequential designation |
385 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-3-642-24797-2">http://dx.doi.org/10.1007/978-3-642-24797-2</a> |
| 912 ## - |
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| -- |
ZDB-2-ENG |
