Deep learning neural networks: design and case studies
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Singapore
World Scientific
[2016]
|
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | Includes index |
Beschreibung: | xvi, 263 Seiten Diagramme 25 cm |
ISBN: | 9789813146440 9789813146457 |
Internformat
MARC
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100 | 1 | |a Graupe, Daniel |e Verfasser |4 aut | |
245 | 1 | 0 | |a Deep learning neural networks |b design and case studies |c Daniel Graupe |
264 | 1 | |a Singapore |b World Scientific |c [2016] | |
264 | 4 | |c © 2016 | |
300 | |a xvi, 263 Seiten |b Diagramme |c 25 cm | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
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500 | |a Includes index | ||
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999 | |a oai:aleph.bib-bvb.de:BVB01-029249051 |
Datensatz im Suchindex
_version_ | 1804176706220589056 |
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adam_text | ACKNOWLEDGEMENTS
PREFACE
CONTENTS
VLL
IX
CHAPTER
1
DEEPLEAMING
NEURAL
NETWORKS:
METHODOLOGY
ANDSCOPE
1
1.1.
DEFINITION
1
1.2.
BRIEFHISTORY
OFDNNANDOFITSAPPLICATIONS
2
1.3.
THESCOPEOFTHE
PRESENT
TEXT
5
1.4.
BRIEFOUTLINE
7
REFERENCES
9
CHAPTER
2
BASICCONCEPTS
OFNEURAI
NETWORKS
13
2.1.
THEHEBBIAN
PRINCIPLE
13
2.2.
THEPERCEPTRON
14
2.3.
ASSOCIATIVE
MEMORY
16
2.4.
WINNER-TAKES-ALL
PRINCIPLE
18
2.5.
THECONVOLUTION
INTEGRAL
18
REFERENCES
20
CHAPTER
3
BACK-PROPAGATION
23
3.1.
THEBACKPROPAGATION
ARCHITECTURE
23
3.2.
DERIVATION
OFTHE
BPALGORITHM
24
3.3.
MODIFIED
BPALGORITHMS
29
REFERENCES
31
XM
XIV
CONTENTS
CHAPTER 4
THECOGNITRON
ANDNEOCOGNITRON
33
4.L.
INTRODUCTION
33
4.2.
PRINCIPLES
OFTHE
COGNITRON
33
4.3.
NETWORK
OPERATION
34
4.4.
COGNITRON
TRAINING
36
4.5.
THENEOCOGNITRON
37
REFERENCES
39
CHAPTER
5
DEEP
LEAMING
CONVOLUTIONAL
NEURAL
NETWORKS
41
5.L.
INTRODUCTION
41
5.2.
CNN
STRUCTURE
42
5.3.
THECONVOLUTIONAL
LAYERS
46
5.4.
BACKPROPAGATION
47
5.5.
RELU
LAYERS
48
5.6.
POOLING
LAYERS
49
5.7.
DROPOUT
50
5.8.
OUTPUT
FCLAYER
51
5.9.
PARAMETER
(WEIGHT)
SHARING
00
5.1O.
APPLICATIONS
52
5.11.
CASE
STUDIES
(WITHPROGRAMCODES)
53
REFERENCES
53
CHAPTER
6
LAMSTAR-1
ANDLAMSTAR-2
NEURAL
NETWORKS
57
6.L.
LAMSTARPRINCIPLES
57
6.2.
LAMSTAR-1
(LNN-1)
71
6.3.
LAMSTAR-2
(LNN-2)
77
6.4.
DATAANALYSIS
WITHLAMSTAR-1
ANDLAMSTAR-2
85
6.5.
LAMSTAR
DATA-BALANCING
PRE-SETTING
PROCEDURE
90
6.6.
COMMENTS
ANDAPPLICATIONS
95
REFERENCES
98
CHAPTER
7
OTHER
NEURAL
NETWORKS
FORDEEP
LEAMING
101
7.L.
DEEP
BOLTZMANN
MACHINES
(DBM)
101
7.2.
DEEP
RECURRENT
LEAMING
NEURAL
NETWORKS
(DRN)
104
7.3.
DECONVOLUTION/WAVELET
NEURAL
NETWORKS
104
REFERENCES
108
CONTENTS
XV
CHAPTER 8
CASESTUDIES
111
8.1.
HUMAN
ACTIVITIES
RECOGNITION
(ABOSE)
111
8.2.
MEDICINE:
PREDICTING
ONSETOFSEIZURES
INEPILEPSY
116
(J
TRAN)
8.3.
MEDICINE:
IMAGE
PROCESSING:
CANCER
DETECTION
117
(DBOSE)
8.4.
IMAGEPROCESSING:
FROM2DIMAGES
TO3D
119
(J
CSOMASUNDARAM)
8.5.
IMAGE
ANALYSIS:
SCENECLASSIFICATION
(NKOUNDINYA)
120
8.6.
IMAGERECOGNITION:
FINGERPRINT
RECOGNITION
1
122
(ADAGGUBATI)
8.7.
IMAGERECOGNITION:
FINGERPRINT
RECOGNITION
2
124
(APONGURU)
8.8.
FACERECOGNITION
(SGANGINENI)
125
8.9.
IMAGE
RECOGNITION
-
BUTTERFLY
SPECIES
CLASSIFICATION
126
(VN
SKADI)
8.10.
IMAGE
RECOGNITION:
LEAFCLASSIFICATION
(PBONDILI)
127
8.11.
IMAGERECOGNITION:
TRAFFIC
SIGNRECOGNITION
129
(DSOMASUNDARAM)
8.12.
INFORMATION
RETRIEVAL:
PROGRAMMING
LANGUAGE
130
CLASSIFICATION
(EWOLFSON)
8.13.
INFORMATION
RETRIEVAL:
DATACLASSIFICATION
FROM
131
TRANSCRIBED
SPOKEN
CONVERSATION
(AKUMAR)
8.14.
SPEECH
RECOGNITION
(MRACHA)
133
8.15.
MUSIC
GENRE
CLASSIFICATION
(YFAN,
CDESHPANDE)
134
8.16.
SECURITY/FINANCE:
CREDIT
CARDFRAUD
DETECTION
135
(FWANG)
8.17.
PREDICTING
LOCATION
FOROILDRILLING
FROM
136
PERMEABILITY
DATAINTESTDRILLS
(ASHUSSAIN)
8.18.
PREDICTION
OFFOREST
FIRES(SRKMURALIDHARAN)
138
8.19.
PREDICTING
PRICEMOVEMENT
INMARKET
MICROSTRUCTURE
139
(XSHI)
8.20.
FAULTDETECTION:
BEARING
FAULTDIAGNOSIS
VIAACOUSTIC
140
EMISSION
(MHE)
CHAPTER
9
CONCLUDING
COMMENTS
141
PROBLEMS
147
XVI
CONTENTS
APPENDICES TOCASE
STUDIES
OFCHAPTER
8
153
A8.I.
HUMAN
ACTIVITY
-
CODES
(ABOSE)
154
A8.2.
PREDICTING
SEIZURES
INEPILEPSY
(JTRAN)
161
A.8.3.
CANCER
DETECTION
(DBOSE)
167
A.8.4.
DEPTH
INFORMATION
FROM2DIMAGES
171
(JCSOMAUNDARAM)
A8.5.
SCENE
CLASSIFICATION
(NKOUDINYA)
176
A8.6.
FINGERPRINT
RECOGNITION
1(ADAGGUBATI)
181
A8.7.
FINGERPRINT
RECOGNITION
2(APONGURU)
182
A8.8.
FACERECOGNOTION
(SGANGINENI)
183
A8.9.
BUTTERFLY
SPECIES
RECOGNITION
(VRSSKADI)
188
A.8.10.
LEAFCLASSIFICATION
(PBONDILI)
198
A8.11.
TRAFFIC
SIGNRECOGNITION
(DSOMASUNDARAM)
200
A8.L2.
PROGRAMMING-LANGUAGE
CLASSIFICATION
(EWOLFSON)
201
A8.L3.
DATACLASSIFICATION
FROMTRANSCRIBED
207
SPOKEN
TEXT(AKUMAR)
A8.14.
SPEECH
RECOGNITION
(MRACHA)
225
A8.15.
MUSIC
GENRE
CLASSIFICATION
(CDESHPANDE)
232
A8.L6.
CREDIT
CARDFRAUD
DETECTION
(FWANG)
237
A8.17.
PREDICTING
SITEFOROILDRILLING
FROMPERMEABILITY
240
DATA(SAHUSSAIN)
A8.L8.
PREDICTING
FOREST
FIRES(SRKMURALIDHARAN)
244
A8.19.
PREDICTING
PRICEMOVEMENT
INMARKET
MICROSTRUCTURE
250
(XSHI)
A8.20.
FAULTDETECTION
(MHE)
250
AUTHOR
INDEX
255
SUBJECT
INDEX
259
|
any_adam_object | 1 |
author | Graupe, Daniel |
author_facet | Graupe, Daniel |
author_role | aut |
author_sort | Graupe, Daniel |
author_variant | d g dg |
building | Verbundindex |
bvnumber | BV043838459 |
classification_rvk | CP 5000 CZ 1300 ST 300 |
ctrlnum | (OCoLC)961905702 (DE-599)BVBBV043838459 |
discipline | Informatik Psychologie |
format | Book |
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id | DE-604.BV043838459 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T07:36:26Z |
institution | BVB |
isbn | 9789813146440 9789813146457 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029249051 |
oclc_num | 961905702 |
open_access_boolean | |
owner | DE-945 DE-29 DE-739 |
owner_facet | DE-945 DE-29 DE-739 |
physical | xvi, 263 Seiten Diagramme 25 cm |
publishDate | 2016 |
publishDateSearch | 2016 |
publishDateSort | 2016 |
publisher | World Scientific |
record_format | marc |
spelling | Graupe, Daniel Verfasser aut Deep learning neural networks design and case studies Daniel Graupe Singapore World Scientific [2016] © 2016 xvi, 263 Seiten Diagramme 25 cm txt rdacontent n rdamedia nc rdacarrier Includes index Lernpsychologie (DE-588)4074166-7 gnd rswk-swf Neuropsychologie (DE-588)4135740-1 gnd rswk-swf Lernpsychologie (DE-588)4074166-7 s Neuropsychologie (DE-588)4135740-1 s DE-604 V:DE-604 application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029249051&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Graupe, Daniel Deep learning neural networks design and case studies Lernpsychologie (DE-588)4074166-7 gnd Neuropsychologie (DE-588)4135740-1 gnd |
subject_GND | (DE-588)4074166-7 (DE-588)4135740-1 |
title | Deep learning neural networks design and case studies |
title_auth | Deep learning neural networks design and case studies |
title_exact_search | Deep learning neural networks design and case studies |
title_full | Deep learning neural networks design and case studies Daniel Graupe |
title_fullStr | Deep learning neural networks design and case studies Daniel Graupe |
title_full_unstemmed | Deep learning neural networks design and case studies Daniel Graupe |
title_short | Deep learning neural networks |
title_sort | deep learning neural networks design and case studies |
title_sub | design and case studies |
topic | Lernpsychologie (DE-588)4074166-7 gnd Neuropsychologie (DE-588)4135740-1 gnd |
topic_facet | Lernpsychologie Neuropsychologie |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029249051&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT graupedaniel deeplearningneuralnetworksdesignandcasestudies |