Cognitive Systems and Signal Processing in Image Processing

Front matter
Copyright
Contributors
A cognitive approach to digital health based on deep learning focused on classification and recognition of white blood cells
Introduction
Literature review
Cognitive systems concepts
Cognitive systems in medical image processing
Cognitive systems in the context of predictive analytics
Neural networks concepts
Convolutional neural network
Deep learning
Metaheuristic algorithm proposal (experiment)
Results and discussion
Conclusions
Future research directions
References
Assessment of land use land cover change detection in multitemporal satellite images using machine learning algorithms
Introduction
Related works
Gaps identified in existing works
Proposed work
Study area
Data collection
Methodology
Maximum likelihood classification
Results and discussions
Maximum likelihood classification
Change detection based on MLC maps
Normalized difference vegetative index classification
Change detection based on NDVI classified maps
Accuracy assessment
Conclusion
References
Further reading
A web application for crowd counting by building parallel and direct connection-based CNN architectures
Introduction
Background
CNN algorithmic model
Data process
Gaussian blur algorithms
Binary space partitioning architecture
Core model structure
Transfer learning
Activation function
Batch normalization
ADCCNet model
Train model by learning data
Data enhancement
Criterion
Gradient optimization
Analyze error
Underfitting and overfitting
Loss value
Training epochs
Learning rate
Verify web applications
Login and register module
Display module
Solve picture module
Take a question module
Experimental results
Future research directions
Conclusion
Appendices
An example of ShangHaiTech dataset .mat file
Verify web applications feature showcase
Acknowledgment
References
A cognitive system for lip identification using convolution neural networks
Introduction
Survey of related work
Summary of existing approaches
Shortcomings of previous work
Motivation
Feature extraction and classification using CNN
Cognitive computing
Convolution network
Database
Results
Conclusion and future work
References
An overview of the impact of PACS as health informatics and technology e-health in healthcare management
Introduction
Review literature on cognitive systems concepts
Cognitive systems in medical image processing
Cognitive systems in the context of predictive analytics
Review literature on implementation of PACS systems
PACS systems application
PACS environments and systems management
PACS extension in the healthcare management
Discussion
Future trends
Conclusions
References
Change detection techniques for a remote sensing application: An overview
Introduction
Remote sensing data
Data preprocessing
Change detection technique
Algebra approach
Image differencing
Image ratioing
Image regression
Vegetation index differencing
Change vector analysis
Transformation approach
Principal component analysis
Kauth-Thomas transformation/tasseled cap transformation
Chi-square transform
Classification approaches
Postclassification comparison
Expectation-maximization algorithm
Hybrid change detection
Artificial neural network
Geographical information system approach
Visual analysis
Other approaches
Conclusion
References
Facial emotion recognition via stationary wavelet entropy and particle swarm optimization
Introduction
Related work of facial emotion recognition
Structure of this chapter
Dataset
Methodology
Stationary wavelet entropy
Single-hidden-layer feedforward neural network
Particle swarm optimization
Implementation
Measure
Experiment results and discussions
Confusion matrix of proposed method
Statistical results
Comparison to state-of-the-art approaches
Conclusions
References
A research insight toward the significance in extraction of retinal blood vessels from fundus images and its various implementations
Introduction
Organization of the chapter
Literature review
Role of retinal blood vessels in disease detection
Retinal pathologies
Cardiovascular diseases
Cerebrovascular diseases
Cancers
Different methods for segmentation
Supervised techniques
Unsupervised technique
Extraction of retinal blood vessels using supervised technique
Materials
Methodology
Preprocessing
Feature extraction
Gabor filtering
Feature vector construction and principal component analysis
Supervised technique
Postprocessing
Result
Qualitative analysis
Quantitative analysis
Performance comparison of our method with the state-of-the-art methods in terms of execution time
Extraction of retinal blood vessels using unsupervised technique
Materials
Proposed method
Preprocessing
Segmentation
Postprocessing
Result
Qualitative analysis
Quantitative analysis
Comparison of our method against existing methods
Conclusion
Future scope
References
Hearing loss classification via stationary wavelet entropy and cat swarm optimization
Introduction
Dataset
Methodology
Stationary wavelet entropy
Single-hidden-layer feedforward neural network
Cat swarm optimization
Implementation
Measure
Experiment results and discussions
Confusion matrix of proposed method
Statistical results
Comparison to state-of-the-art approaches
Conclusions
References
Early detection of breast cancer using efficient image processing algorithms and prediagnostic techniques: A detailed approach
Introduction
Literature review
Breast cancer: A brief introduction
Overview of breast cancer
Symptoms of breast cancer
Categories of breast cancer
Inflammatory breast cancer
Triple-negative breast cancer
Metastatic breast cancer
Male breast cancer
Breast cancer stages
Diagnosis of breast cancer
Breast cancer treatment
Surgery
Radiation therapy
Chemotherapy
Hormone therapy
Medications
Risk factors for breast cancer
Breast cancer survival rate
Breast cancer prevention
Lifestyle factors
Breast cancer screening
Preemptive treatment
Breast test
Self-test
Breast test by a doctor
Breast cancer awareness
Cognitive approaches in breast cancer techniques
Cognitive image processing
Knowledge-based vision systems
Integration of knowledge bases in vision systems
Image processing, annotation, and retrieval
Human activity recognition
Medical images analysis
Proposed methodology
Workflow
Algorithms used
Results and discussion
Conclusion
References
Groundnut leaves and their disease, deficiency, and toxicity classification using a machine learning approach
Introduction
Groundnut crop
Major diseases
Major deficiencies
Disease, deficiency, and toxicity management
Lack of accurate detection
Literature review
Methodology
Image dataset
Image acquisition
Preprocessing of the acquired image
Image segmentation
Clustering technique
K-means clustering algorithm
Feature extraction
Classification
Support vector machine classifier
Random forest classifier
K-nearest neighbor classifier
Decision tree classifier
Neural network classifier
Results and discussion
Experimental results
Performance evaluation
Classification matrix
Conclusion
Acknowledgment
References
EEG-based computer-aided diagnosis of autism spectrum disorder
Introduction
Related work
Proposed work
Performance analysis
Conclusion
References
Toward improving the accuracy in the diagnosis of schizophrenia using functional magnetic resonance imaging (fMRI)
Introduction
Literature review
Methodology
Database
Subject
fMRI and acquisition of fMRI
Preprocessing
Principal component analysis
Independent component analysis
Feature extraction
Local binary pattern
Modified volume local binary pattern
Feature selection
Classification
LDA, NN, and SVM
Performance evaluation
Results and discussion
Performance evaluation by varying the number of ICs
Using LDA classifier
Using NN classifier
Using SVM classifier
Performance evaluation using different types of LDA, NN, and SVM
Performance evaluation using LDA classifier with different types of discriminants
Performance analysis using NN classifier with various distance measures
Performance estimation using SVM classifier with other types of kernels
Discussion
Comparison with the existing system
Conclusion
References
An artificial intelligence mediated integrated wearable device for diagnosis of cardio through remote monitoring
Introduction
Related work
Proposed work
Feature extraction
ECG filtering
Principal component analysis
Steps in principal components analysis
BPN classifier
Convolutional neural network with Boltzman
Decision tree classifier
K-SVD with MOD
Pan-Tomkinson algorithm
Performance analysis
Conclusion
References
Deep learning for accident avoidance in a hostile driving environment
Introduction
Literature review
Research challenges and motivation
Semantic segmentation
Segmentation using deep learning architecture
Detection
Evolution of deep models for object detection
Region-based network framework
Object recognition
Image processing dataset
Natural language processing dataset
Audio/speech processing dataset
Deep learning architectures
Results and discussion
Semantic segmentation using deep learning
Vehicle detection using deep learning
Vehicle recognition using deep learning
Conclusion and future work
References
Risk analysis of coronavirus patients who have underlying chronic cancer
Introduction
Related work
About COVID-19 with chronic diseases
Experimental analysis
Method and data source
Dataset
Evaluation metrics
Implementation and result
Result of the study
Discussion
Conclusion
References
Index
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