• Purab Alok Jain
• Deepesh Singh
• Sugandh Kumar
• Govind Somani
• Ruhi Patankar

Owing to the advancement in artificial intelligence computing, deep-learning neural networks have been used for transforming low resolution images into high-resolution images. This transformation is referred to as Super-resolution. Super-resolution has many applications worldwide like enhancing optical-microscope photographic images, satellite imagery, the study of the galaxy, etc. This technique can be used to fight against the growing number of COVID cases. COVID is presenting itself in the form of different strains, some of which are not detectable using RT-PCR (Reverse Transcription Polymerase Chain Reaction) or Rapid Antigen Test, however X-Rays or CT-Scans have higher chances of detecting them. These scans sometimes miss little details because of the blurriness/low-resolution of the image. This problem can be overcome by using the Fast Super-Resolution Convolutional Neural Network (FSRCNN). The purpose of this paper is to discuss a model that using FSRCNN and classification can detect Covid status in patients along with providing other vital information to the user. For the transformation of a low-resolution image into a high-resolution image, FSRCNN and for classifying whether the person is having coronavirus or not a Convolutional Neural Network (CNN) is used. Our models are trained and tested on 4 datasets, which are Set5, Set14, covid-chestxray-dataset, and chest-xray-pneumonia. Our results depict that after applying super-resolution on the X-Rays or the CT-Scans, the classification of COVID-19 attained a higher accuracy. These were the results after running the model for 20 epochs. Hence, with the help of the FSRCNN model, the classification of COVID-19 is much easier and accurate as compared to without the image super-resolution technique.

"Web Application for COVID-19 Detection using Super Resolution", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.g90-g93, June-2021, Available :http://www.jetir.org/papers/JETIR2106840.pdf

"Web Application for COVID-19 Detection using Super Resolution", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppg90-g93, June-2021, Available at : http://www.jetir.org/papers/JETIR2106840.pdf