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035   $a(DE-He213)978-981-15-6572-4
035   $a(PPN)250212854
035   $a(EXLCZ)994100000011401188
100   $a20200826d2020      u|             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aIntelligent Systems and Methods to Combat Covid-19$b[electronic resource] /$fedited by Amit Joshi, Nilanjan Dey, K. C. Santosh
205   $a1st ed. 2020.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020.
215   $a1 online resource (xii, 91 pages) $cillustrations
225 1 $aSpringerBriefs in Computational Intelligence,$x2625-3704
311   $a981-15-6571-6 
327   $aChapter 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.
330   $aThis book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.
410  0$aSpringerBriefs in Computational Intelligence,$x2625-3704
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aHealth informatics
606   $aControl engineering
606   $aRobotics
606   $aMechatronics
606   $aBig data
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060
606   $aControl, Robotics, Mechatronics$3https://scigraph.springernature.com/ontologies/product-market-codes/T19000
606   $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aHealth informatics.
615  0$aControl engineering.
615  0$aRobotics.
615  0$aMechatronics.
615  0$aBig data.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aHealth Informatics.
615 24$aControl, Robotics, Mechatronics.
615 24$aBig Data.
676   $a610.28563
702   $aJoshi$b Amit$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aDey$b Nilanjan$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aSantosh$b K. C$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910416084003321
996   $aIntelligent Systems and Methods to Combat Covid-19$92129765
997   $aUNINA