Data fusion: concepts and ideas
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Springer
2012
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XIV, 344 Seiten Illustrationen, Diagramme |
| ISBN: | 9783642272219 |
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| 264 | 1 | |a Berlin |b Springer |c 2012 | |
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| adam_text | IMAGE 1
CONTENTS
1 INTRODUCTION 1
1.1 DEFINITION 1
1.2 SYNERGY 1
1.3 MULTI-SENSOR DATA FUSION STRATEGIES 3
1.3.1 FUSION TYPE 3
1.3.2 SENSOR CONFIGURATION 4
1.3.3 INPUT/OUTPUT CHARACTERISTICS 6
1.4 FORMAL FRAMEWORK 7
1.4.1 MULTI-SENSOR INTEGRATION 9
1.5 CATASTROPHIC FUSION 10
1.6 ORGANIZATION 12
1.7 FURTHER READING 13
REFERENCES 14
2 SENSORS 15
2.1 INTRODUCTION 15
2.2 SMART SENSOR 16
2.3 LOGICAL SENSORS 17
2.4 INTERFACE FILE SYSTEM (IFS) 18
2.4.1 INTERFACE TYPES 19
2.4.2 TIMING 19
2.5 SENSOR OBSERVATION 21
2.5.1 SENSOR UNCERTAINTY 22
2.6 SENSOR CHARACTERISTICS 24
2.7 SENSOR MODEL 25
2.8 FURTHER READING 28
REFERENCES 29
3 ARCHITECTURE 31
3.1 INTRODUCTION 31
3.2 FUSION NODE 32
HTTP://D-NB.INFO/1017296723
IMAGE 2
X CONTENTS
3.2.1 PROPERTIES 34
3.3 SIMPLE FUSION NETWORKS 35
3.3.1 SINGLE FUSION CELL 35
3.3.2 PARALLEL NETWORK 3 6
3.3.3 SERIAL NETWORK 37
3.3.4 ITERATIVE NETWORK 39
3.4 NETWORK TOPOLOGY 4 0
3.4.1 CENTRALIZED 41
3.4.2 DECENTRALIZED 42
3.4.3 HIERARCHICAL 45
3.5 SOFTWARE 47
3.6 FURTHER READING 48
REFERENCES 4 9
4 COMMON REPRESENTATIONAL FORMAT 51
4.1 INTRODUCTION 51
4.2 SPATIAL-TEMPORAL TRANSFORMATION 55
4.3 GEOGRAPHICAL INFORMATION SYSTEM 57
4.3.1 SPATIAL COVARIANCE FUNCTION 59
4.4 COMMON REPRESENTATIONAL FORMAT 6 0
4.5 SUBSPACE METHODS 67
4.5.1 PRINCIPAL COMPONENT ANALYSIS 67
4.5.2 LINEAR DISCRIMINANT ANALYSIS 7 0
4.6 MULTIPLE TRAINING SETS 7 4
4.7 SOFTWARE 77
4.8 FURTHER READING 77
REFERENCES 78
5 SPATIAL ALIGNMENT 83
5.1 INTRODUCTION 83
5.2 IMAGE REGISTRATION 84
5.3 MUTUAL INFORMATION 85
5.3.1 HISTOGRAM ESTIMATION 85
5.3.2 KERNEL DENSITY ESTIMATION 87
5.3.3 REGIONAL MUTUAL INFORMATION 89
5.4 OPTICAL FLOW 91
5.5 FEATURE-BASED IMAGE REGISTRATION 9 4
5.6 RESAMPLE/INTERPOLATION 94
5.7 PAIRWISE TRANSFORMATION 97
5.8 UNCERTAINTY ESTIMATION * 99
5.9 IMAGE FUSION 100
5.9.1 FUSION O F PET AND MRI IMAGES 100
5.9.2 SHAPE AVERAGING 101
5.10 MOSAIC IMAGE 103
5.11 SOFTWARE 105
IMAGE 3
CONTENTS XI
5.12 FURTHER READING 105
REFERENCES 106
6 TEMPORAL ALIGNMENT 109
6.1 INTRODUCTION 109
6.2 DYNAMIC TIME WARPING I L L
6.3 DYNAMIC PROGRAMMING 113
6.3.1 DERIVATIVE DYNAMIC TIME WARPING 115
6.3.2 CONTINUOUS DYNAMIC TIME WARPING 117
6.4 ONE-SIDED DTW ALGORITHM 117
6.4.1 VIDEO COMPRESSION 118
6.4.2 VIDEO DENOISING 121
6.5 MULTIPLE TIME SERIES 122
6.6 SOFTWARE 122
6.7 FURTHER READING 122
REFERENCES 123
7 SEMANTIC ALIGNMENT 125
7.1 INTRODUCTION 125
7.2 ASSIGNMENT MATRIX 127
7.3 CLUSTERING ALGORITHMS 130
7.4 CLUSTER ENSEMBLES 132
7.4.1 CO-ASSOCIATION MATRIX 134
7.5 SOFTWARE 136
7.6 FURTHER READING 137
REFERENCES 137
8 RADIOMETRIC NORMALIZATION 139
8.1 INTRODUCTION 139
8.2 SCALES OF MEASUREMENT 140
8.3 DEGREE-OF-SIMILARITY SCALES 141
8.4 RADIOMETRIC NORMALIZATION 148
8.5 BINARIZATION 150
8.6 PARAMETRIC NORMALIZATION FUNCTIONS 157
8.7 FUZZY NORMALIZATION FUNCTIONS 157
8.8 RANKING 158
8.9 CONVERSION TO PROBABILITIES 161
8.9.1 MULTI-CLASS PROBABILITY ESTIMATES * 164
8.10 SOFTWARE 166
8.11 FURTHER READING 166
REFERENCES 167
IMAGE 4
XII CONTENTS
9 BAY ESIAN INFERENCE 171
9.1 INTRODUCTION 171
9.2 BAYESIAN ANALYSIS 171
9.3 PROBABILITY MODEL 173
9.4 A POSTERIORI DISTRIBUTION 173
9.4.1 STANDARD PROBABILITY DISTRIBUTION FUNCTIONS 175
9.4.2 CONJUGATE PRIORS 175
9.4.3 NON-INFORMATIVE PRIORS 177
9.4.4 MISSING DATA 179
9.5 GAUSSIAN MIXTURE MODEL 181
9.6 MODEL SELECTION 184
9.6.1 LAPLACE APPROXIMATION 185
9.6.2 BAYESIAN MODEL AVERAGING 187
9.7 COMPUTATION* 188
9.7.1 MARKOV CHAIN MONTE CARLO 188
9.8 SOFTWARE 189
9.9 FURTHER READING 190
REFERENCES 190
10 PARAMETER ESTIMATION 193
10.1 INTRODUCTION 193
10.2 PARAMETER ESTIMATION 193
10.3 BAYESIAN CURVE FITTING 197
10.4 MAXIMUM LIKELIHOOD 200
10.5 LEAST SQUARES 202
10.6 LINEAR GAUSSIAN MODEL 204
10.6.1 LINE FITTING 206
10.6.2 CHANGE POINT DETECTION 208
10.6.3 PROBABILISTIC SUBSPACE 211
10.7 GENERALIZED MILLMAN FORMULA 213
10.8 SOFTWARE 215
10.9 FURTHER READING 215
REFERENCES 215
11 ROBUST STATISTICS 217
11.1 INTRODUCTION 217
11.2 OUTLIERS - 218
11.3 ROBUST PARAMETER ESTIMATION 222
11.3.1 STUDENT-F FUNCTION 222
11.3.2 GOOD-AND-BAD LIKELIHOOD FUNCTION 225
11.3.3 GAUSSIAN PLUS CONSTANT 227
11.3.4 UNCERTAIN ERROR BARS 228
11.4 CLASSICAL ROBUST ESTIMATORS 231
11.4.1 LEAST MEDIAN O F SQUARES 231
11.5 ROBUST SUBSPACE TECHNIQUES * 232
IMAGE 5
CONTENTS XIII
11.6 ROBUST STATISTICS IN COMPUTER VISION 233
11.7 SOFTWARE 236
11.8 FURTHER READING 236
REFERENCES 237
12 SEQUENTIAL BAYESIAN INFERENCE 239
12.1 INTRODUCTION 239
12.2 RECURSIVE FILTER 240
12.3 KALMAN FILTER 244
12.3.1 PARAMETER ESTIMATION 249
12.3.2 DATA ASSOCIATION 250
12.3.3 NEAREST NEIGHBOUR FILTER 251
12.3.4 PROBABILISTIC DATA ASSOCIATION FILTER 254
12.3.5 MODEL INACCURACIES : 255
12.3.6 MULTI-TARGET TRACKING 257
12.4 EXTENSIONS O F THE KALMAN FILTER 257
12.4.1 ROBUST KALMAN FILTER 257
12.4.2 EXTENDED KALMAN FILTER 259
12.4.3 UNSCENTED KALMAN FILTER 260
12.4.4 SWITCHING KALMAN FILTER 262
12.5 PARTICLE FILTER * 264
12.6 MULTI-SENSOR MULTI-TEMPORAL DATA FUSION 264
12.6.1 MEASUREMENT FUSION 264
12.6.2 TRACK-TO-TRACK FUSION 266
12.7 SOFTWARE 269
12.8 FURTHER READING 269
REFERENCES 271
13 BAYESIAN DECISION THEORY 273
13.1 INTRODUCTION 273
13.2 PATTERN RECOGNITION 273
13.3 NAIVE BAYES CLASSIFIER 277
13.3.1 REPRESENTATION 278
13.3.2 PERFORMANCE 278
13.3.3 LIKELIHOOD 280
13.4 VARIANTS 282
- 13.4.1 FEATURE SELECTION 282
13.4.2 FEATURE EXTRACTION 285
13.4.3 TREE-AUGMENTED NAIVE BAYES CLASSIFER 285
13.5 MULTIPLE NAIVE BAYES CLASSIFIERS 286
13.6 ERROR ESTIMATION 287
13.7 PAIRWISE NAIVE BAYES CLASSIFIER 289
13.8 SOFTWARE 289
13.9 FURTHER READING 290
REFERENCES 290
IMAGE 6
XIV CONTENTS
14 ENSEMBLE LEARNING 295
14.1 INTRODUCTION 295
14.2 BAYESIAN FRAMEWORK 295
14.3 EMPIRICAL FRAMEWORK 298
14.4 DIVERSITY TECHNIQUES 299
14.4.1 BAGGING 300
14.4.2 BOOSTING 301
14.4.3 SUBSPACE TECHNIQUES 301
14.4.4 SWITCHING CLASS LABELS 302
14.5 DIVERSITY MEASURES 302
14.5.1 ENSEMBLE SELECTION 303
14.6 CLASSIFIER TYPES 304
14.7 COMBINATION STRATEGIES 305
14.8 SIMPLE COMBINERS 306
14.8.1 IDENTITY COMBINERS 306
14.8.2 RANK COMBINERS 310
14.8.3 BELIEF COMBINERS 311
14.9 META-LEARNERS 313
14.10BOOSTING 314
14.11 RECOMMENDATIONS 318
14.12SOFTWARE 318
14.13FURTHER READING 319
REFERENCES 319
15 SENSOR MANAGEMENT 323
15.1 INTRODUCTION 323
15.2 HIERARCHICAL CLASSIFICATION 324
15.2.1 SENSOR CONTROL 324
15.2.2 SENSOR SCHEDULING 325
15.2.3 RESOURCE PLANNING 326
15.3 SENSOR MANAGEMENT TECHNIQUES 326
15.3.1 INFORMATION-THEORETIC CRITERIA 326
15.3.2 BAYESIAN DECISION-MAKING 328
15.4 FURTHER READING 330
15.5 POSTSCRIPT 330
REFERENCES 331
BACKGROUND MATERIAL 333
INDEX 337
|
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| id | DE-604.BV040099657 |
| illustrated | Illustrated |
| indexdate | 2024-08-01T11:12:28Z |
| institution | BVB |
| isbn | 9783642272219 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024956235 |
| oclc_num | 796202575 |
| open_access_boolean | |
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| physical | XIV, 344 Seiten Illustrationen, Diagramme |
| publishDate | 2012 |
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| publisher | Springer |
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| spellingShingle | Mitchell, H. B. Data fusion concepts and ideas Datenfusion (DE-588)4582612-2 gnd Multisensor (DE-588)4257775-5 gnd Messwertverarbeitung (DE-588)4038804-9 gnd |
| subject_GND | (DE-588)4582612-2 (DE-588)4257775-5 (DE-588)4038804-9 |
| title | Data fusion concepts and ideas |
| title_auth | Data fusion concepts and ideas |
| title_exact_search | Data fusion concepts and ideas |
| title_full | Data fusion concepts and ideas H. B. Mitchell |
| title_fullStr | Data fusion concepts and ideas H. B. Mitchell |
| title_full_unstemmed | Data fusion concepts and ideas H. B. Mitchell |
| title_short | Data fusion |
| title_sort | data fusion concepts and ideas |
| title_sub | concepts and ideas |
| topic | Datenfusion (DE-588)4582612-2 gnd Multisensor (DE-588)4257775-5 gnd Messwertverarbeitung (DE-588)4038804-9 gnd |
| topic_facet | Datenfusion Multisensor Messwertverarbeitung |
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| work_keys_str_mv | AT mitchellhb datafusionconceptsandideas |
Inhaltsverzeichnis
THWS Würzburg Teilbibliothek SHL, Raum I.2.11
| Signatur: |
1340 ZQ 3120 M681(2) |
|---|---|
| Exemplar 1 | nicht ausleihbar Verfügbar Bestellen |