|
|
|
|
| LEADER |
03702nmm a2200409 u 4500 |
| 001 |
EB001904212 |
| 003 |
EBX01000000000000001067118 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
201103 ||| eng |
| 020 |
|
|
|a 9783030552589
|
| 100 |
1 |
|
|a Hassanien, Aboul-Ella
|e [editor]
|
| 245 |
0 |
0 |
|a Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach
|h Elektronische Ressource
|c edited by Aboul-Ella Hassanien, Nilanjan Dey, Sally Elghamrawy
|
| 250 |
|
|
|a 1st ed. 2020
|
| 260 |
|
|
|a Cham
|b Springer International Publishing
|c 2020, 2020
|
| 300 |
|
|
|a XI, 307 p. 169 illus., 130 illus. in color
|b online resource
|
| 505 |
0 |
|
|a Coronavirus Spreading Forecasts based on Susceptible-Infectious- Recovered and Linear Regression Model -- Virus Graph and COVID-19 Pandemic: A Graph Theory Approach -- Nonparametric Analysis of Tracking Data in the Context of COVID-19 Pandemic -- Visualization and prediction of trends of Covid-19 pandemic during early outbreak in India using DNN and SVR -- The Detection of COVID-19 in CT Medical Images: A Deep Learning Approach -- COVID-19 Data Analysis and Innovative approach in Prediction of Cases -- Detection of COVID-19 using Chest Radiographs with Intelligent Deployment Architecture -- COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor -- Why are Generative Adversarial Networks Vital for Deep Neural Networks? A Case Study on COVID-19 Chest X-Ray Images -- Artificial intelligence against COVID-19: A meta-analysis of current research -- Insights of Artificial Intelligence to Stop Spread of COVID-19 -- AI based Covid19 analysis-A pragmatic approach -- Artificial Intelligence and Psychosocial Support during the COVID-19 Outbreak -- Role of The Accurate Detection of Core Body Temperature in The Early Detection of Coronavirus -- The effect Coronavirus Pendamic on Education into Electronic Multi-Modal Smart Education -- An H2O’s Deep Learning-inspired model based on Big Data analytics for Coronavirus Disease (COVID-19) Diagnosis -- Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique -- Stacking Deep Learning for Early COVID-19 Vision Diagnosis
|
| 653 |
|
|
|a Big data
|
| 653 |
|
|
|a Biomedical engineering
|
| 653 |
|
|
|a Computational intelligence
|
| 653 |
|
|
|a Artificial Intelligence
|
| 653 |
|
|
|a Computational Intelligence
|
| 653 |
|
|
|a Biomedical Engineering and Bioengineering
|
| 653 |
|
|
|a Data Engineering
|
| 653 |
|
|
|a Artificial intelligence
|
| 653 |
|
|
|a Epidemiology
|
| 653 |
|
|
|a Engineering / Data processing
|
| 653 |
|
|
|a Big Data
|
| 700 |
1 |
|
|a Dey, Nilanjan
|e [editor]
|
| 700 |
1 |
|
|a Elghamrawy, Sally
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a Studies in Big Data
|
| 028 |
5 |
0 |
|a 10.1007/978-3-030-55258-9
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-55258-9?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 620.00285
|
| 520 |
|
|
|a This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.
|