COVID-19 Detector Using Deep Learning
Mohammed Ali Shaik, Sachin kumar Koppula, Mohammed Rafiuddin, Bonagiri Sai Preethi
Abstract
This paper attempt to overcome the existing Covid 19 detection challenge, which aims to predict whether the tested person is a covid positive or covid negative. This research work has utilized the “Covid chest X-Ray” images dataset and the CT scan images dataset of Covid affected people and healthy people from the Kaggle website. Further, the proposed research work has utilized a couple CNN models on the collected dataset to see if the input image was Covid positive or negative. This research study will construct four CNN architectures as a group: ResNet-50, Inception-v3, and Xception. These models will be trained by using chest X-Ray and CT scan images, and then a Web API will be developed by using Flask so that the users may interact within themselves via a website. And the user may self-identify whether he/she is Covid positive or negative by uploading any chest X-Ray or CT scan image of the individual.