Computer-aided Learning and Analysis for COVID-19 Disease
Published on 22. March 2022
128 pages
978-1-80382-872-5 (ISBN)
Description
Computer-aided Learning and Analysis for COVID-19 Disease
More details
Content
- Cover1
- Guest editorial
- COVID-19 prediction through X-ray images using various layers in convolutional neural network
- Hybrid artificial bee colony and glow worm algorithm for energy efficient cluster head selection in wireless sensor networks
- Empirical path loss models at 433 MHz in Himalayan snow for health monitoring
- An intrusion detection system for health-care system using machine and deep learning
- Diagnosis of COVID-19 through blood sample using ensemble genetic algorithms and machine learning classifier
- COVID-19 image transmission using convolutional neural networks based algorithms for medical applications
- Diagnosis of COVID-19 using 3D CT scans and vaccination for COVID-19
- Multi-criteria analysis of social isolation barriers amid COVID-19 using fuzzy AHP
- Early flood detection and rescue using bioinformatic devices, internet of things (IOT) and Android application
- Machine learning improvements to compressive sensing for speech enhancement in hearing aid applications
- Automatic epileptic seizure detection using LSTM networks
- Formation of the counter intelligence strategy of Ukraine: national and legal dimension
- Role of machine learning in changing social and business eco-system - a qualitative study to explore the factors contributing to competitive advantage during COVID pandemic
- The rise of 3D E-Commerce: the online shopping gets real with virtual reality and augmented reality during COVID-19
- Integrating hyperreal literature with CALL in English language curriculum for engineering studies in India: an empirical study of the impact on students' learning
