Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing.
Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iii 6. Contributors - p. xiii 7. Chapter 1. A cognitive approach to digital health based on deep learning focused on classification and recognition of white blood cells - p. 1 8. Chapter 2. Assessment of land use land cover change detection in multitemporal satellite images using machine learning algorithms - p. 37 9. Chapter 3. A web application for crowd counting by building parallel and direct connection-based CNN architectures - p. 47 10. Chapter 4. A cognitive system for lip identification using convolution neural networks - p. 87 11. Chapter 5. An overview of the impact of PACS as health informatics and technology e-health in healthcare management - p. 101 12. Chapter 6. Change detection techniques for a remote sensing application: An overview - p. 129 13. Chapter 7. Facial emotion recognition via stationary wavelet entropy and particle swarm optimization - p. 145 14. Chapter 8. A research insight toward the significance in extraction of retinal blood vessels from fundus images and its various implementations - p. 169 15. Chapter 9. Hearing loss classification via stationary wavelet entropy and cat swarm optimization - p. 203 16. Chapter 10. Early detection of breast cancer using efficient image processing algorithms and prediagnostic techniques: A detailed approach - p. 244 17. Chapter 11. Groundnut leaves and their disease, deficiency, and toxicity classification using a machine learning approach - p. 271 18. Chapter 12. EEG-based computer-aided diagnosis of autism spectrum disorder - p. 277 19. Chapter 13. Toward improving the accuracy in the diagnosis of schizophrenia using functional magnetic resonance imaging (fMRI) - p. 293 20. Chapter 14. An artificial intelligence mediated integrated wearable device for diagnosis of cardio through remote monitoring - p. 319 21. Chapter 15. Deep learning for accident avoidance in a hostile driving environment - p. 337 22. Chapter 16. Risk analysis of coronavirus patients who have underlying chronic cancer - p. 359 23. Index - p. 375
Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing.
Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iii 6. Contributors - p. xiii 7. Chapter 1. A cognitive approach to digital health based on deep learning focused on classification and recognition of white blood cells - p. 1 8. Chapter 2. Assessment of land use land cover change detection in multitemporal satellite images using machine learning algorithms - p. 37 9. Chapter 3. A web application for crowd counting by building parallel and direct connection-based CNN architectures - p. 47 10. Chapter 4. A cognitive system for lip identification using convolution neural networks - p. 87 11. Chapter 5. An overview of the impact of PACS as health informatics and technology e-health in healthcare management - p. 101 12. Chapter 6. Change detection techniques for a remote sensing application: An overview - p. 129 13. Chapter 7. Facial emotion recognition via stationary wavelet entropy and particle swarm optimization - p. 145 14. Chapter 8. A research insight toward the significance in extraction of retinal blood vessels from fundus images and its various implementations - p. 169 15. Chapter 9. Hearing loss classification via stationary wavelet entropy and cat swarm optimization - p. 203 16. Chapter 10. Early detection of breast cancer using efficient image processing algorithms and prediagnostic techniques: A detailed approach - p. 244 17. Chapter 11. Groundnut leaves and their disease, deficiency, and toxicity classification using a machine learning approach - p. 271 18. Chapter 12. EEG-based computer-aided diagnosis of autism spectrum disorder - p. 277 19. Chapter 13. Toward improving the accuracy in the diagnosis of schizophrenia using functional magnetic resonance imaging (fMRI) - p. 293 20. Chapter 14. An artificial intelligence mediated integrated wearable device for diagnosis of cardio through remote monitoring - p. 319 21. Chapter 15. Deep learning for accident avoidance in a hostile driving environment - p. 337 22. Chapter 16. Risk analysis of coronavirus patients who have underlying chronic cancer - p. 359 23. Index - p. 375
