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:
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Provides a state-of-the-art computer vision application in the digital health care industry
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Reviews advances in computer vision and data science technologies for analyzing information on human function and disability
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Includes practical implementation of computer vision application using recent tools and software
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Explores computer vision-enabled medical/clinical data security in the cloud
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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.
Preface
Chapter 1 : Introduction to Computer Vision Aided Data Analytics on Healthcare Industry 4.0
Chapter 2 : Deep Learning Techniques for Foetal and Infant Data Processing in a Medical Context
Chapter 3 : Analysis of Detecting Brain Tumors Using Deep Learning Algorithms
Chapter 4 : Secured Data Dissemination in Real-Time Healthcare System
Chapter 5 : Modality Classification of Human Emotions
Chapter 6 : COVID-19 Alert Zone Detection Using OpenCV
Chapter 7 : Feature Fusion Model for Heart Disease Diagnosis
Chapter 8 : Deep Learning and Its Applications in Healthcare
Chapter 9 : Future of Computer Vision Application in Digital Healthcare
Chapter 10 : Study of Computer Vision Applications in Healthcare Industry 4.0
Index
