|
|
|
|
| LEADER |
03104nmm a2200421 u 4500 |
| 001 |
EB001900780 |
| 003 |
EBX01000000000000001063689 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
200911 ||| eng |
| 020 |
|
|
|a 9789811565724
|
| 100 |
1 |
|
|a Joshi, Amit
|e [editor]
|
| 245 |
0 |
0 |
|a Intelligent Systems and Methods to Combat Covid-19
|h Elektronische Ressource
|c edited by Amit Joshi, Nilanjan Dey, K. C. Santosh
|
| 250 |
|
|
|a 1st ed. 2020
|
| 260 |
|
|
|a Singapore
|b Springer Nature Singapore
|c 2020, 2020
|
| 300 |
|
|
|a XII, 91 p. 21 illus., 18 illus. in color
|b online resource
|
| 505 |
0 |
|
|a Chapter 1. Data Analytics: COVID-19 Prediction using Multimodal Data -- Chapter 2. COVID-19 Apps: Privacy and security concerns -- Chapter 3. Coronavirus Outbreak: Multi-objective Prediction and Optimization -- Chapter 4. AI-Enabled Framework to Prevent COVID-19 from Further Spreading -- Chapter 5. Artificial Intelligence Enabled Robotic Drones for COVID-19 Outbreak -- Chapter 6. Understanding and Analysis of Enhanced COVID-19 Chest X-Ray Images -- Chapter 7. Deep Learning-based COVID-19 Diagnosis and Trend Predictions -- Chapter 8. COVID-19: Loose Ends -- Chapter 9. Social Distancing and Artificial Intelligence- Understanding the Duality in the times of Covid-19 -- Chapter 10. Post Covid-19 and Business Analytics
|
| 653 |
|
|
|a Big data
|
| 653 |
|
|
|a Health Informatics
|
| 653 |
|
|
|a Control, Robotics, Automation
|
| 653 |
|
|
|a Computational intelligence
|
| 653 |
|
|
|a Medical informatics
|
| 653 |
|
|
|a Artificial Intelligence
|
| 653 |
|
|
|a Computational Intelligence
|
| 653 |
|
|
|a Control engineering
|
| 653 |
|
|
|a Artificial intelligence
|
| 653 |
|
|
|a Robotics
|
| 653 |
|
|
|a Big Data
|
| 653 |
|
|
|a Automation
|
| 700 |
1 |
|
|a Dey, Nilanjan
|e [editor]
|
| 700 |
1 |
|
|a Santosh, K. C.
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a SpringerBriefs in Computational Intelligence
|
| 028 |
5 |
0 |
|a 10.1007/978-981-15-6572-4
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-15-6572-4?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.3
|
| 520 |
|
|
|a This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals
|