Accessibility, 48

Accidental concept drift, 228–229, 232–233, 237

Accuracy, 6, 218

Activation function, 94

Active attack phenomena, 207, 207f

Adversarial networks, 185

AI, See Artificial intelligence (AI)

AIH, See Hospital Admission Authorization (AIH)

AlexNet, 252

Alzheimer’s dementia

Alzheimer’s Disease Neuroimaging Initiative dataset, 161

Amazon, 38–39, 41

ANNs, See Artificial neural networks (ANNs)

APAC, See High Complexity Procedure Authorization (APAC)

Apache Hadoop, 41–42

Apache MXNet, 187, 188t

Apache Spark, 43–45, 45f, 78

Application programming interface (API), 100–101, 209

AR Face database, 24

Area under curve (AUC), 144–145

Artificial intelligence (AI), 64–66, 71, 73–74, 83, 119, 130, 135, 138, 158–159

Artificial learning, 131f

Artificial neural networks (ANNs), 135, 183–184, 213–214, 215f

Artificial neuron, 94–95, 96f, 213

Aspect extraction, 53–55

Attention-based aspect extraction structure, 54, 55f

AUC, See Area under curve (AUC)

Autoencoders, 51, 185, 187

Availability, 209

Average or mean pooling, 247, 248f

Bag of features (BOF), 142–143

Basophils, 133–134

Bayesian hypotheses, 135

Bayesian networks, 73–74

Bernsen’s binary method, 15–16

Bi-LSTM, See Bidirectional long short-term memory (Bi-LSTM)

Bidirectional long short-term memory (Bi-LSTM), 52–53

Big data, 64–66, 74–77, 74f, 81

BigDL, 78

Binary image, 15–16

Biometric aging, 29

Biometric cryptosystems, 27–28

Biometric recognition, 2–6, 26

Biometric security, 1–2

Biometric system, attack possibilities in, 25f

Biometrics, 1

Blood, 132, 134

Body sensor networks (BSNs), 115–116, 124

BOF, See Bag of features (BOF)

Bone marrow, 132

Botnet attack, 209

Brazilian Public Health System, 201–202

BSNs, See Body sensor networks (BSNs)

Cached system, 229

CAD, See Computer-aided diagnostic (CAD)

Cancelable biometrics, 26–27

Carcinoid tumor, 241–242

CART, See Classification and Regression Tree (CART)

Casia.v4 iris database, 23

CDA, See Confirmatory data analysis (CDA)

Cell

Cerebrospinal fluid (CSF), 158–159

Chronic diseases, 113–114, 118

Circulatory system, 134

Classification and Regression Tree (CART), 229–230

Classification stage, 269

Clustering, 73–74

CMU-PIE, 23

CN, See Cognitive normal (CN)

CNN, See Convolutional neural network (CNN)

CNN-F, See Convolutional neural network-fast (CNN-F)

CNTK, See Microsoft Cognitive Toolkit

Cognitive normal (CN), 161

Color

Color FERET, 23

Common voice (Mozilla), 24

Comparative analysis among different modalities, 28–29

Computed tomography (CT), 143

Computer vision, 66, 69f

Computer-aided diagnostic (CAD), 143

Concept drift, 228–230, 233

Concept-adapting Very Fast Decision Tree (CVFDT), 228–229

Conceptual architecture, 164f

Confidentiality, 208

Confirmatory data analysis (CDA), 37–38

Contextual learning, 104

Conventional rule-based models, 119–120

ConvNet, 162, 164, 169, 243–244

Convolution, 141, 164–165, 165f

Convolution layer, 162–165, 217–218

Convolutional neural network (CNN), 2–3, 5, 9f, 21–22, 51, 70–71, 76–77, 130, 139–141, 140f, 162, 170–172, 185, 190–193, 214–215, 216f, 242–250

Convolutional neural network-fast (CNN-F), 16

Cosine similarity, 199

Creative Senz3D camera, 270

CRISP-DM, See CRoss Industry Standard Process for Data Mining (CRISP-DM)

CRM, See Customer relationship management (CRM)

CRoss Industry Standard Process for Data Mining (CRISP-DM), 50

Cross-sectional MRI Data in Young, Middle-Aged, Non-demented, and Demented Older Adults (OASIS-1), 170, 171t

Cross-validation (CV), 106

CSF, See Cerebrospinal fluid (CSF)

CT, See Computed tomography (CT)

CUDA deep neural network library (CuDNN), 187

Curse of dimensionality, 51

Customer relationship management (CRM), 56–59

CV, See Cross-validation (CV)

CVFDT, See Concept-adapting Very Fast Decision Tree (CVFDT)

Cyber security

Cytoplasm, 133–134

Data, 63

Data mining, 49–51

Data stream-CART (dsCART), 229–231

Dataset description, 201–202

DBM, See Deep Boltzmann machine (DBM)

DBN, See Deep belief network (DBN)

DCNN, See Deep CNN (DCNN)

DDOS attack, See Distributed denial of service attack (DDOS attack)

Decision trees (DT), 119–120, 135, 229–230

Deep autoencoders, 217, 217f, 222–223

Deep belief network (DBN), 76–77, 174, 217

Deep Boltzmann machine (DBM), 161

Deep CNN (DCNN), 12–13

Deep convolutional neural network, 160

Deep learning, 2–3, 63–65, 90–91, 94–95, 130, 159, 183, 211f

Deep learning-based detection and classification of adenocarcinoma cell nuclei

Deep learning-based frameworks, 212–213

Deep neural network (DNN), 66, 67f, 160, 251–252

Deep Patient, 189–190

Deep Record, 189–190

Deep similarity learning model, 189

Deep-stacked autoencoder, 161

DeepCare, 189–190, 198

DeepIrisNet, 18–19

deeplearning4j, 187, 188t

DeepPore model, 15–16

Degree of subjectivity, 90

Dementia, 157

Denial of service (DOS), 209, 219

Depth image datasets, 267

Descriptive models, 50–51

Digital images, 131–132, 139

Digital smear diagnosis of blood smears, 129

Dimensionality, 68–70

Discriminative models, 185

Distributed computing, 41–45

Distributed denial of service attack (DDOS attack), 209, 221–223

DNN, See Deep neural network (DNN)

Domain-specific (kidney-related) dataset, 193

DOS, See Denial of service (DOS)

Drosophila melanogaster muscles, 142

dsCART, See Data stream-CART (dsCART)

DT, See Decision trees (DT)

Dynamic signatures, 22

E-CART algorithm, See Efficient Classification and Regression Tree algorithm (E-CART algorithm)

E-commerce, 82

E-CVFDT, See Efficient-Concept-adapting Very Fast Decision Tree (E-CVFDT)

EDA, See Exploratory data analysis (EDA)

Edge detection algorithm, 21–22

Edge intelligence, 83

EER, See Equal error rate (EER)

Efficient Classification and Regression Tree algorithm (E-CART algorithm), 233–235, 234t

Efficient-Concept-adapting Very Fast Decision Tree (E-CVFDT), 228–229, 231–232

Electronic health records (EHRs), 189–193, 195

Electronic Product Code technology (EPC technology), 121

Emergent SOM, 57

Emoticons, 101

End-to-end deep learning, 2

Ensemble method, 174

Eosinophils, 133–134

EPC technology, See Electronic Product Code technology (EPC technology)

Equal error rate (EER), 6

Erythrocytes, 132–133

Euclidean distance, 199

Exploratory data analysis (EDA), 37–38

F1-score, 260

Face recognition, 12–13

Facebook, 38–41, 89

Failure recovery, 209

False alarming rate (FAR), 218

False match rate (FMR), 6

False nonmatch rate (FNMR), 6

FAR, See False alarming rate (FAR)

Faster R-CNN algorithm, cell detection using, 255–257

Feature extraction, 51, 63–64, 90, 92–93, 139, 271

Feature map, 170–172

Feature-based machine learning, 18–19, 28–29

Feed-forward networks, 8–10

Feed-forward neural network, 187, 197–198

FEI, 23

Filters, 139

Finger pore detection, 15–16

Fingerprint recognition, 13–16

Flattened process, 250

Flow-based intrusion detection systems, 221

FMR, See False match rate (FMR)

FNMR, See False nonmatch rate (FNMR)

Four vs. of big data, 40, 40f

Frontal dementia, 157

Fully connected layer, 169–170, 169f

Fusion, 267

FVC2002, 24

FVC2004, 24

FVC2006, 24

Gait analysis, 21

Gait recognition, 21–23

Gated recurrent unit (GRU), 161–162

Gaussian blur, 7

Gaussian decision tree (GDT), 233

Gaussian skin color model, 266

Generative adversarial networks, 217–218

Generative models, 97–99, 185

Geometric features, 269

GFS, See Google File System (GFS)

Gluon, 212

Google, 38–41

Google dataset, 24

Google File System (GFS), 41

Gradual concept drift, 228–229, 232–233, 235

Graphics processing unit (GPU), 3, 187

GRU, See Gated recurrent unit (GRU)

Hadoop Distributed File System (HDFS), 41–42

Hand gesture recognition studies, 265

Hand symbols, 265

Handcrafted feature-driven basic machine learning classifiers, 97–98

Hard biometrics, 12–20

HCNN, See Hierarchical convolutional neural network (HCNN)

HDFS, See Hadoop Distributed File System (HDFS)

Healthcare, 148

Healthcare data, 193

Hematology, 132–134

Hidden layers, 94–95

Hierarchical convolutional neural network (HCNN), 18–19

High Complexity Procedure Authorization (APAC), 201–202

HIS, See Hospital information system (HIS)

Histogram-based image segmentation, 268

Histopathological image analysis, 120

Hive, 37, 42–43

Hoeffding tree, 230

Hog face detection, See Viola–Jones algorithm

Hospital Admission Authorization (AIH), 201–202

Hospital information system (HIS), 119–120

HTTP, See Hypertext transfer protocol (HTTP)

Hypertext transfer protocol (HTTP), 123, 223

ICD-10, See International Classification of Diseases (ICD-10)

ICT, See Information and communication technology (ICT)

Identification, 12–13

Image preprocessing stage, 267

Image processing, 143

Image recognition, 139

Image segmentation, 270

Inception-V3 model, 172–174

Inductive logic programming, 73–74

Industry 4.0, 80

Information and communication technology (ICT), 114

Insider threat, 220

Instagram, 41

Instantaneous concept drift, 228–229, 232–233, 235–236

Integrity, 208–209

Intel Core i3 processor, 145–147

Intelligence, 66

International Classification of Diseases (ICD-10), 200–201

Internet of Medical Things, 113

Internet of Things (IoT), 77, 113–114, 207, 222

Internet Protocol spoofing attack (IP spoofing attack), 209

Internet systems, 118–119

Intraclass variations, 5

Intrusion detection systems, 219

IoT, See Internet of Things (IoT)

IP spoofing attack, See Internet Protocol spoofing attack (IP spoofing attack)

Iris recognition, 18–19

Iris Recognition Immigration System, 18

K-nearest neighbor classification, 229

Kaggle dataset, 24

Keras, 187, 188t

Kernels, 139

Labati’s model, 15–16

Labeled data, 72–73, 90–91

Language recognition, 135

Large-scale visualization, 38

LDP, See Local direction pattern (LDP)

Learning

Leukemia, 130

Leukocyte(s), 131–134

Leukocytosis, 151

Lewy body dementia, 157

Lexical semantics, 99

LibriSpeech, 23

Linear algebra, 213

Linear discriminant analysis, 54

Local direction pattern (LDP), 21–22

Long short-term memory (LSTM), 96, 161–162, 189–193

Loss function, 56

LSTM, See Long short-term memory (LSTM)

LSTMIC, See Long short-term memory (LSTM)

LSTTM, 22

Lung adenocarcinoma (LUAD), 144–145

LUSC, See Squamous cell carcinoma of lung (LUSC)

Lymph nodes, 132

Lymphocyte/leukocytes, 133–134

Machine learning, 2, 51, 63, 65–66, 71–76, 81, 119, 135, 136f, 139, 159, 210–211, 251

Macrophages, 132–133

Magnetic resonance imaging (MRI), 158

Mainstream methods, 53

Man-in-the-middle attack, 209, 210f

Manhattan distance, 199

Mapping characteristics, 139

MapReduce Framework, 41–43, 42f

Massively parallel processing, 41

Max pooling, 247, 247f

McDiarmid’s inequality, 230–231

MCI, See Mild cognitive impairment (MCI)

Mean blur, 7

Mel frequency cepstral coefficient (MFCC), 20

Memory, 93

MENet, 29–31

MENet, See Minutiae extraction network (MENet)

Methodology proposal, 145–147

MFCC, See Mel frequency cepstral coefficient (MFCC)

MFCN, See Multiscaled fully convoluted network (MFCN)

Microsoft Cognitive Toolkit, 187, 188t

Microsoft ResNet, 70–71

Middleware system, 118–119

Mild cognitive impairment (MCI), 158

Minimum pooling, 247, 248f

Minutiae, 13–15

Minutiae extraction network (MENet), 16

MLP, See Multilayer perceptron (MLP)

MNIST, See Modified National Institute of Standards and Technology (MNIST)

Model training, 72, 197–200

Modern-day technology, 119

Modified National Institute of Standards and Technology (MNIST), 76–77

Monocytes, 133–134

MRI, See Magnetic resonance imaging (MRI)

Multibit planes, 19–20

Multilayer perceptron (MLP), 187

Multimedia data mining, 52–53

Multimodal biometrics, 29

Multiple-layer deep learning models, 120

Multiscaled fully convoluted network (MFCN), 18–19

MXNet, 212

National Laboratory of Pattern Recognition, 24

Natural language processing (NLP), 66, 68f, 79, 185, 215

Natural neuron, 94f

Neural networks, 63–64, 64f, 70, 131f

Neuroimaging information, 159

Neuron, 70, 213–214

Neuropsychological information, 159

Neutrophils, 133–134

NIGHT-care RFID system, 121

NLP, See Natural language processing (NLP)

Nonlinear diffusion, 26

One-shot enrollment, 12–13

Opcodes, 220

Open Access Series of Imaging Studies (OASIS), 170

Open System Interconnection model, 222

OpenEHRBenchmark Dataset (ORBDA), 193, 201–202

Optimality, 266

Padding, 166, 246

Palmprint recognition, 16–18

Parkinson’s disease, 157

Passive attack phenomena, 207, 207f

Perceptron, 94–95, 213

Performance evaluation, 202–203

PET, See Positron emission tomography (PET)

Phishing attack, 209, 210f

Physiological parameters, 114, 122

Plasma, 132

Platelets, 134

PMap, 253

Point of vulnerabilities, 209

PolyU database, 23

Pooling layer, 139–141, 166–168, 246–248

Positron emission tomography (PET), 158

Precise recognition, deep learning methodology for, 12–20

Precision, 218

Predictive analysis, 130

Predictive models, 50–51

Pretrained AlexNet network, 253

Privacy, 207–208

Proposed deep learning framework, 99, 100f

Python, 102

Python 3.7, 131–132, 145–147

PyTorch, 187, 188t, 212

QlikView, 38

Radial basis function neural networks, 185

Radio frequency identification device tag (RFID tag), 118–119, 121, 124–125

Random neural networks, 219

RBM, See Restricted Boltzmann machine (RBM)

Real-time monitoring, 125

Recall, 218

Recurrent neural networks (RNNs), 2–3, 5–6, 11f, 21–22, 52, 95–96, 104, 161–162, 185–187, 214–215, 217

Red blood cells, 132–133

Reference vectors, 58

Region proposal network (RPN), 256

Regularized stacked denoising auto-encoder-softmax layer (RSDAE-SM), 190–193

Reinforced learning, 73–74

Reinforcement learning, 73

ReLu, 164, 170–172

Representation learning, 197–198

ResNet architecture, 16

ResNet-101, cell classification with, 257

Resting-state functional magnetic resonance imaging (rs-fMRI), 160

Restricted Boltzmann machine (RBM), 161, 185

Retweet, 89, 96–97

Retweet prediction, 90

Reverse bandwidth floods, 223

RFID tag, See Radio frequency identification device tag (RFID tag)

RGB, 267

“RMSProp” Optimizer, 172–174

RNNs, See Recurrent neural networks (RNNs)

Robust algorithms, 21

RPN, See Region proposal network (RPN)

rs-fMRI, See Resting-state functional magnetic resonance imaging (rs-fMRI)

RSDAE-SM, See Regularized stacked denoising auto-encoder-softmax layer (RSDAE-SM)

Rule-based methods, 54

“SAME” padding, 246

SC-CNN, See Spatial constrained convolution neural network (SC-CNN)

Scientific review, 141–145

SDAE, See Stacked denoising auto-encoder (SDAE)

SDN, See Software-defined networking (SDN)

Security, 207–208

Segmentation method, 143

Segmentation stage, 268–269

Self-improvement, 135

Self-organizing maps (SOMs), 51, 57–59

Semantics, 99

Semisupervised learning, 73, 80

Service attack, denial of, 220f

Session hijacking, 209

Seven Vs of big data analysis, 37, 40

SHA-512 cryptographic hashing, 12–13

Siamese networks, 21

Siamese neural network, 10–12, 12f

Siamese-LSTM, 22

Sign language recognition system, 266

Signature recognition, 22

Similarity learning, 198–200

Simple Service Discovery Protocol, 123

Single neuron network, 94–95

Single perceptron, 93

Smartphone devices, 116

Snapchat, 41

Sobel edge detector, 7

Social media platforms, 89

Soft biometrics, 23

Softmax

Software and hardware configuration, 202

Software-defined networking (SDN), 222

SOMs, See Self-organizing maps (SOMs)

Sonnet, 212

Spam

Spark ML, 44

Spatial constrained convolution neural network (SC-CNN), 260

Speech recognition, 66, 68f, 79

Spleen, 132

Splitting data, 196

Spoof protection, 24–26

Spoofing, 24

SQL database, 40

Squamous cell carcinoma of lung (LUSC), 144–145

Squared error of regression line, 25

SqueezeNet, 19–20

SSAE, See Stacked sparse autoencoder (SSAE)

Stacked autoencoders, 220–221

Stacked denoising auto-encoder (SDAE), 190–193

Stacked restricted Boltzmann machines, 220–221

Stacked sparse autoencoder (SSAE), 260

Stride, 165

Structured information, 75

Subsampling, 139

Supervised learning, 185, 189, 197–198

Supervised techniques, 54

Support vector machine (SVM), 119–120

SYN flood attacks, 223

Tableau, 37

Template protection, 26–28

Tensor processing unit (TPU), 3

Tensor representation model, 77

TensorFlow, 187, 188t, 211–212

TFBS, See Transcription factor binding site (TFBS)

TFs, See Transcription factors (TFs)

Theano, 187, 188t

Thresholding methods, 268

TPU, See Tensor processing unit (TPU)

Traditional SOM, 57

Transcription factor binding site (TFBS), 142

Transcription factors (TFs), 141

Transfer learning, 83

Transmission Control Protocol, 123

Tumor development speed, 242

Tweet

Twitter, 38–40, 89, 92, 97

Twitter Streaming API, 100–101

Two-phase strategy of feature fusion, 267

Ubiris.v2 iris database, 23

Unlabeled data, 73, 90–91

Unstructured data, 138

Unsupervised learning, 185, 197

URLs, 101

User Datagram Protocol, 123

Users, 47

V1 (Job Tracker and Task Tracker), 41–42

V2 (YARN), 41–42

“VALID” padding, 246

Value of data, 41, 75

Variability of data, 41

Variety of data, 39, 75

Vein recognition, 19–20

Velocity of data, 39–40, 39f, 75

Verification in biometric recognition, 5

Very Fast Decision Tree (VFDT), 228–229

VGG-Face CNN, 13

VGG16 network, 70–71, 256–257

VGGNet-based algorithm, 15–16

Viola–Jones algorithm, 12–13

Visual clustering, 56–57

Visualization of data, 41

Voice recognition, 20–21

Volume of data, 40, 75

Wang’s u-net model, 15–16

Ward distance, 59

Ward’s clustering, 59

Wearable devices, 116

Weber local binary, 25

Wellness tourism, 126

White blood cells, 133–134

Wireless sensor networks (WSNs), 121, 123

Word expletive, 103–104

YouTube, 41

Zernike moment features, 269

Zero padding, 246