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Full Description
This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring.
Features:
Provides a state-of-the-art computer vision application in the digital health care industry
Reviews advances in computer vision and data science technologies for analyzing information on human function and disability
Includes practical implementation of computer vision application using recent tools and software
Explores computer vision-enabled medical/clinical data security in the cloud
Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google
This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.
Contents
1. Introduction to Computer Vision Aided Data Analytics in Healthcare Industry 4.0 2. Deep Learning Techniques for Foetal and Infant Data Processing in a Medical Context 3. Analysis of Detecting Brain Tumors Using Deep Learning Algorithms 4. Secured Data Dissemination in a Real-Time Health Care System 5. Modality Classification of Human Emotion 6. COVID-19 Alert Zone Detection Using OpenCV 7. Feature Fusion Model for Heart Disease Diagnosis 8. Deep Learning and Its Applications in Health Care 9. Future of Computer Vision Application in Digital Healthcare 10. Study of Computer Vision Applications in Healthcare Industry 4.0
