An Efficient Deep Learning Classifiers Algorithm for Examining Public Perception of Covid SOPs
Keywords:
Deep Learning, datasets, machine learning, COVID, virus, WHO, public perceptionAbstract
In December 2019, Wuhan, China, reported the first coronavirus case, confirming the current pandemic. Following that, it swept across the entire world. The leading cause of this disease is still unknown, though. Governments are emphasizing physical distance and wearing masks in public places. The people mostly ignore the safety SOPs, which results in a surge in infected people rates and a healthcare burden on the national economy. Through the identification of face masks, this study used machine learning and deep learning models to analyse sentiment. Then, it compared the effectiveness of machine learning and deep learning techniques RMFD, SMFD, and LFW using three modern datasets. We used two deep learning algorithms, Convolutional Neural Network and Visual Geometry Group, and one machine learning algorithm Histogram of Oriented Gradient-Support vector machine, for accurate facemask detection. The reason for using a machine learning algorithm is that it has achieved promising results regarding face mask detection accuracy when trained with a large amount of data. The findings of a comparative analysis with accuracy results have been discussed at the end, and the conclusion is that the proposed framework produced more excellent accuracy results.
References
Bilgin S, Kurtkulagi O, Bakir Kahveci G, Taslamacioglu Duman T. Atak Tel B. Millennium pandemic: a review of coronavirus disease (COVID-19). Exp Biomed Res. 2020; 3(2): 117–125.
Al-Qaness Mohammed AA, Ewees Ahmed A, Hong Fan, Mohamed Abd El Aziz. Optimization method for forecasting confirmed cases of COVID-19 in China. J Clin Med. 2020; 9(3): 674.
Tomar Anuradha, Neeraj Gupta. Prediction for the spread of COVID-19 in India and effectiveness of preventive measures. Sci Total Environ. 2020; 728: 138762.
Feroze Navid. Assessing the future progression of COVID-19 in Iran and its neighbors using Bayesian models. Infect Dis Model. 2021; 6: 343–350.
Conceição Pedro. Food security and human development in Africa: strategic considerations and directions for further research. Afr Dev Rev. 2011; 23(2): 237–246.
Atif M, Malik I, Asif M, Qamar-Uz-Zaman M, Ahmad N, Scahill S. Drug safety in Pakistan. InDrug safety in developing countries 2020 Jan 1 (pp. 287–325). Academic Press.
Barnett-Howell Zachary, Ahmed Mushfiq Mobarak. The benefits and costs of social distancing in rich and poor countries. arXiv preprint arXiv: 2004.04867. 2020.
Chirwa Gowokani Chijere, "Who knows more, and why?" Explaining socioeconomic-related inequality in knowledge about HIV in Malawi. Sci Afr. 2020; 7: e00213.
Dkhar Sabira Aalia, Ruqia Quansar, Sheikh Mohd Saleem, Muhammad Salim Khan S. Knowledge, attitude, and practices related to COVID-19 pandemic among social media users in J&K, India. Indian J Public Health. 2020; 64(6): 205–210.
Abraham Bejoy, Nair Madhu S. Computer-aided detection of COVID-19 from X-ray images using multi-CNN and Bayesnet classifier. Biocybern Biomed Eng. 2020; 40(4): 1436–1445.
Jignesh Chowdary G, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal. Face masks detection using transfer learning of inceptionv3. In International Conference on Big Data Analytics; Cham: Springer; 2020; 81–90.
Inamdar Madhura, Ninad Mehendale. Real-Time Face Mask Identification Using Facemasknet Deep Learning Network. Available at SSRN 3663305. 2020.
Alghaili Mohammed, Zhiyong Li, Ali Hamdi AR. FaceFilter: Face Identification with Deep Learning and Filter Algorithm. Sci Program. 2020; 2020: 7846264.
Zulfikar Wiwit Aditama, Vonna Auliansyah. Public perception of physical distancing in preventing the spread of coronavirus disease (COVID-19) in the city of Banda Aceh in 2020. Executive Editor (EE). 2020; 11(7): 1579.
Raamkumar, Aravind Sesagiri, Soon Guan Tan, Hwee Lin Wee. Use of health belief model–based deep learning classifiers for covid-19 social media content to examine public perceptions of physical distancing: Model development and case study. JMIR Public Health Sur. 2020; 6(3): e20493.
Jarvis Christopher I, Kevin Van Zandvoort, Amy Gimma, Kiesha Prem, Petra Klepac, James Rubin G, John Edmunds W. Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK. BMC Med. 2020; 18(1): 124(1–10).
Seale Holly, Heywood Anita E, Julie Leask, Meru Sheel, Susan Thomas, Durrheim David N, Katarzyna Bolsewicz, Rajneesh Kaur. COVID-19 is rapidly changing: Examining public perceptions and behaviors in response to this evolving pandemic. PloS One. 2020; 15(6): e0235112.
Doogan Caitlin, Wray Buntine, Henry Linger, Samantha Brunt. Public perceptions and attitudes toward COVID-19 nonpharmaceutical interventions across six countries: A topic modeling analysis of Twitter data. J Medical Internet Res. 2020; 22(9): e21419.
Griffis Heather, Asch David A, Andrew Schwartz H, Lyle Ungar, Buttenheim Alison M, Barg Frances K, Nandita Mitra, Merchant Raina M. Using social media to track geographic variability in language about diabetes: Infodemiology analysis. JMIR diabetes. 2020; 5(1): e14431.
Yehuda Rachel, Amy Lehrner. Intergenerational transmission of trauma effects: putative role of epigenetic mechanisms. World Psychiatry. 2020; 17(3): 243–257.
Giallonardo Vincenzo, Gaia Sampogna, Valeria Del Vecchio, Mario Luciano, Umberto Albert, Claudia Carmassi, Giuseppe Carrà. The impact of quarantine and physical distancing following COVID-19 on mental health: study protocol of a multicentric Italian population trial. Front Psychiatry. 2020; 11: 533.
Islam Nazrul, Sharp Stephen J, Gerardo Chowell, Sharmin Shabnam, Ichiro Kawachi, Ben Lacey, Massaro Joseph M, D'Agostino Ralph B, Martin White. Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries. bmj. 2020; 370: m2743.
Arora Vineet M, Marius Chivu, Andrew Schram, David Meltzer. Implementing physical distancing in the hospital: a key strategy to prevent nosocomial transmission of COVID-19. J Hosp Med. 2020; 15(5): 290–291.
Al-Hanawi Mohammed K, Khadijah Angawi, Noor Alshareef, Qattan Ameerah MN, Helmy Hoda Z, Yasmin Abudawood, Mohammed Alqurashi. Knowledge, attitude and practice toward COVID-19 among the public in the Kingdom of Saudi Arabia: a cross-sectional study. Front Public Health. 2020; 8: 217.
Yanti Budi, Eko Wahyudi, Wahiduddin Wahiduddin, Revi Gama Hatta Novika, Yuliana Mahdiyah Da'at Arina, Natalia Sri Martani, Nawan Nawan. Community knowledge, attitudes, and behavior towards social distancing policy as prevention transmission of COVID-19 in indonesia. Journal Administrasi Kesehatan Indonesia (JAKI). 2020; 8(2): 4–14.
Singh D, Kumar V, Vaishali, Kaur M. Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks. Eur J Clin Microbiol Infect Dis (Off Publ Eur Soc Clin Microbiol). 2020; 39(7): 1379–1389.
Liu T, Kang L, Li Y, Huang J, Guo Z, Xu J, Xin W, et al. Simultaneous Detection of Seven Human Coronaviruses by Multiplex PCR and MALDI-TOF MS. Covid. 2021; 2(01): 5–17.
Fuss FK, Weizman Y, Tan AM. COVID-19 pandemic: how effective are preventive control measures and is a complete lockdown justified? A comparison of countries and states. Covid. 2021; 2(1): 18–46.
Hirota K, Mayahara T, Fujii Y, Nishi K. Asymptomatic Hypoxemia as a Characteristic Symptom of Coronavirus Disease: A Narrative Review of Its Pathophysiology. COVID. 2022; 2(1): 47–59.