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EDL-COVID: Ensemble Deep Learning for COVID-19 Case Detection From Chest X-Ray Images
171
Zitationen
7
Autoren
2021
Jahr
Abstract
, an ensemble deep learning model employing deep learning and ensemble learning. The EDL-COVID model is generated by combining multiple snapshot models of COVID-Net, which has pioneered in an open-sourced COVID-19 case detection method with deep neural network processed chest X-ray images, by employing a proposed weighted averaging ensembling method that is aware of different sensitivities of deep learning models on different classes types. Experimental results show that EDL-COVID offers promising results for COVID-19 case detection with an accuracy of 95%, better than COVID-Net of 93.3%.
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Autoren
Institutionen
- Tianjin University(CN)
- Nanyang Technological University(SG)
- Asia University(TW)
- Thapar Institute of Engineering & Technology(IN)
- Providence University(TW)
- Feng Chia University(TW)
- University of Petroleum and Energy Studies(IN)
- Wuhan University of Technology(CN)
- Wuhan University of Science and Technology(CN)
- Singapore University of Technology and Design(SG)
- King Abdulaziz University(SA)