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Vector mosquito image classification using novel RIFS feature selection and machine learning models for disease epidemiology

Authors: Furqan Rustam, Aijaz Ahmad Reshi, Wajdi Aljedaani, Abdulaziz Alhossan, Abid Ishaq, Shabana Shafi, Ernesto Lee, Ziyad Alrabiah, Hessa Alsuwailem, Ajaz Ahmad, Vaibhav Rupapara
Publication date: 2021/9/20
Journal: Saudi Journal of Biological Sciences
Publisher: Elsevier


Every year about one million people die due to diseases transmitted by mosquitoes. The infection is transmitted to a person when an infected mosquito stings, injecting the saliva into the human body. The best possible way to prevent a mosquito-borne infection till date is to save the humans from exposure to mosquito bites. This study proposes a Machine Learning (ML) and Deep Learning based system to detect the presence of two critical disease spreading classes of mosquitoes such as the Aedes and Culex. The proposed system will effectively aid in epidemiology to design evidence-based policies and decisions by analyzing the risks and transmission. The study proposes an effective methodology for the classification of mosquitoes using ML and CNN models. The novel RIFS has been introduced which integrates two types of feature selection techniques – the ROI-based image filtering and the wrappers-based …


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Scholar articles
F Rustam, AA Reshi, W Aljedaani, A Alhossan, A Ishaq… – Saudi Journal of Biological Sciences, 2021
January 5, 2022
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