Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System |
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Authors: | Mahmoud Ragab Mohammed W. Al-Rabia Sami Saeed Binyamin Ahmed A. Aldarmahi |
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Affiliation: | 1.School of Mechanical and Electrical Engineering, Beijing Institute of Graphic Communication, Beijing, 102600, China2 Postal Industry Technology R&D Center, Beijing Institute of Graphic Communication, Beijing, 102600, China3 Collage of Electronic Information and Automation, Civil Aviation University of China, Tianjin, 300300, China |
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Abstract: | With the increasing and rapid growth rate of COVID-19 cases, the healthcare scheme of several developed countries have reached the point of collapse. An important and critical steps in fighting against COVID-19 is powerful screening of diseased patients, in such a way that positive patient can be treated and isolated. A chest radiology image-based diagnosis scheme might have several benefits over traditional approach. The accomplishment of artificial intelligence (AI) based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition systems. This study develops an Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System (IFFA-DTLMS). The proposed IFFA-DTLMS model majorly aims at identifying and categorizing the occurrence of COVID19 on chest radiographs. To attain this, the presented IFFA-DTLMS model primarily applies densely connected networks (DenseNet121) model to generate a collection of feature vectors. In addition, the firefly algorithm (FFA) is applied for the hyper parameter optimization of DenseNet121 model. Moreover, autoencoder-long short term memory (AE-LSTM) model is exploited for the classification and identification of COVID19. For ensuring the enhanced performance of the IFFA-DTLMS model, a wide-ranging experiments were performed and the results are reviewed under distinctive aspects. The experimental value reports the betterment of IFFA-DTLMS model over recent approaches. |
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Keywords: | COVID-19 artificial intelligence intelligent systems deep learning decision making |
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