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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