Detecting Covid-19 from Chest X-ray using Transfer Learning

The novel Coronavirus has been the most harmful disaster that nobody could have ever imagined. Currently it has become a fatal epidemic, citing fears concerning the health infrastructural facilities on the market, considering the need to take a look at a vast population. The foremost common diagnostic tests available as of now are Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and Rapid Antigen Testing (RAT), which is usually preferred to acquire the results in a quick span of time. However, there are some drawbacks to RT-PCR testing and RAT testing, like relying only on these 2 ways might be challenging and it becomes increasingly tough for many nations to get the requisite number of testing kits, and there are some occurrences of false-positive results. Chest X-rays, additionally to RT-PCR testing, will be a helpful technique for containing the spread of COVID, as patients can receive the results quickly and take required measures. The tensor flow-based CNN method has been projected to classify chest x-ray images. The projected model has been trained and tested on the ready dataset consequently, a viable answer has been presented, that is that the development of a COVID-19 detection system that might assist medical specialists with the reports and then the consultants will come back to a call. Within the medical field, transfer learning has established to be the foremost economical technology and has excelled within the field of image processing, which makes it the more effective approach for our use case.