Computational modeling and data analysis in COVID-19 research / edited by Chhabi Rani Panigrahi, Bibudhendu Pati, Mamata Rath and Rajkumar Buyya
Machine learning implementations in COVID-19 / Kabita Kumari, S.K. Pahuja, and Sanjeev Kumar -- Analysis of COVID-19 data using consensus clustering technique / Arko Banerjee, Sunandana Mukherjee, Chhabi Rani Panigrahi, Bibudhendu Pati, and Rajib Mall -- MoBMGAN : modified GAN-based transfer learning for automatic detection of COVID-19 cases using chest X-ray images / Rajashree Nayak and Bunil Ku. Balabantaray -- Application and progress of drone technology in the COVID-19 pandemic : a comprehensive review / Vasundhara Saraf, Lipsita Senapati, and Tripti Swarnkar -- Smart war on COVID-19 and global pandemics : integrated AI and blockchain ecosystem / Anil D Pathak, Debasis Saran, Sibani Mishra, Madapathi Hitesh, Sivaiah Bathula, and Kisor K Sahu -- Machine learning based text mining in social media for COVID-19 / Tajinder Singh and Madhu Kumari -- Containing the spread of COVID-19 with IoT : a visual tracing approach / Pallav Kumar Deb , Sudip Misra, Anandarup Mukherjee, and Aritra Bandopadhyay -- Crowd-sourced centralized thermal imaging for isolation and quarantine / Sudershan Kumar, Prabuddha Sinha, and Sujata Pal -- Block chain technology for limiting the impact of pandemic : challenges and prospects / Suchismita Swain, Oyekola Peter, Ramasamy Adimuthu, and Kamalakanta Muduli -- A study on mathematical and computational models in the context of COVID-19 / Meera Joshi -- A detailed study on AI-based diagnosis of novel coronavirus from radiograph images / Malaya Kumar Nath and Aniruddha Kanhe -- Data analytics for COVID-19 / Shreyas Mishra..
| Medienart: |
E-Book |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
Boca Raton: CRC Press, Taylor & Francis Group, ; 2021 |
| Ausgabe: |
First edition. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Rani Panigrahi, Chhabi [HerausgeberIn] |
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| Links: |
www.taylorfrancis.com [lizenzpflichtig] |
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| ISBN: |
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| Umfang: |
1 online resource |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
1765053250 |
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| 250 | |a First edition. | ||
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| 520 | |a Machine learning implementations in COVID-19 / Kabita Kumari, S.K. Pahuja, and Sanjeev Kumar -- Analysis of COVID-19 data using consensus clustering technique / Arko Banerjee, Sunandana Mukherjee, Chhabi Rani Panigrahi, Bibudhendu Pati, and Rajib Mall -- MoBMGAN : modified GAN-based transfer learning for automatic detection of COVID-19 cases using chest X-ray images / Rajashree Nayak and Bunil Ku. Balabantaray -- Application and progress of drone technology in the COVID-19 pandemic : a comprehensive review / Vasundhara Saraf, Lipsita Senapati, and Tripti Swarnkar -- Smart war on COVID-19 and global pandemics : integrated AI and blockchain ecosystem / Anil D Pathak, Debasis Saran, Sibani Mishra, Madapathi Hitesh, Sivaiah Bathula, and Kisor K Sahu -- Machine learning based text mining in social media for COVID-19 / Tajinder Singh and Madhu Kumari -- Containing the spread of COVID-19 with IoT : a visual tracing approach / Pallav Kumar Deb , Sudip Misra, Anandarup Mukherjee, and Aritra Bandopadhyay -- Crowd-sourced centralized thermal imaging for isolation and quarantine / Sudershan Kumar, Prabuddha Sinha, and Sujata Pal -- Block chain technology for limiting the impact of pandemic : challenges and prospects / Suchismita Swain, Oyekola Peter, Ramasamy Adimuthu, and Kamalakanta Muduli -- A study on mathematical and computational models in the context of COVID-19 / Meera Joshi -- A detailed study on AI-based diagnosis of novel coronavirus from radiograph images / Malaya Kumar Nath and Aniruddha Kanhe -- Data analytics for COVID-19 / Shreyas Mishra. | ||
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| 650 | 0 | |a SARS (Disease) | |
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| 650 | 0 | |a COVID-19 (Disease) |x Research | |
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| 650 | 2 | |a Severe Acute Respiratory Syndrome | |
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