• Ms. Y.Divya teja
• Mr.M.Vinay Kumar

Pneumonia is a respiratory infection caused by bacteria or viruses that affects many people, particularly in developing and impoverished countries with high levels of pollution, unsanitary living conditions, and overcrowding, as well as inadequate medical infrastructure. Pneumonia produces pleural effusion, a disease in which fluids fill the lung and cause difficulties breathing. Early detection of pneumonia is critical for curative therapy and increasing survival rates. The most often used approach for detecting pneumonia is chest X-ray imaging. However, examining chest X-rays is a difficult task that is vulnerable to subjective variability. We created a computer-aided diagnosis system for automatic pneumonia detection utilizing chest X-ray pictures in this study. To deal with the lack of accessible data, we used deep transfer learning and created a Convolutional Neural Network (CNN) model together with the four transfer learning methods: CovXNet, RNN, and VGG16. Whereas in the existing methods, ResNet 50 is employed, which does not have the required accuracy and might be improved. As a result, the current strategy, along with other transfer learning methods, is offered. The proposed method was tested using a public ally available pneumonia X-ray dataset.learning, image processing, CNN, VGG-16, and squeeze net are some of the related terms.

Pneumonia, Chest X-ray images. Deep Learning, CNN, CovXNet, RNN, VGG16

"PNEUMONIA DETECTION USING CNN FROM CHEST X RAYS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.g715-g719, July-2023, Available :http://www.jetir.org/papers/JETIR2307698.pdf

"PNEUMONIA DETECTION USING CNN FROM CHEST X RAYS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppg715-g719, July-2023, Available at : http://www.jetir.org/papers/JETIR2307698.pdf