Springer, 2021. — 416 p. — ISBN 978-3-030-75489-1.
This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach —the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach.
Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.
Deep Architectures in Visual Transfer Learning
Deep Reinforcement Learning: A New Frontier in Computer Vision Research
Deep Learning for Data-Driven Predictive Maintenance
Multi-criteria Fuzzy Goal Programming Under Multi Uncertainty
Skeleton-Based Human Action Recognition on Large-Scale Datasets
Sensor-Based Human Activity and Behavior Computing
Radar-Based Non-Contact Physiological Sensing
Biomedical Radar and Antenna Systems for Contactless Human Activity Analysis
Contactless Monitoring for Healthcare Applications
Personalized Patient Safety Management: Sensors and Real-Time Data Analysis
Electrical Impedance Tomography Based Lung Disease Monitoring
Image Analysis with Machine Learning Algorithms to Assist Breast Cancer Treatment
Role-Framework of Artificial Intelligence
Time Series Analysis
Challenges Ahead in Healthcare Applications for Vision and Sensors