Chest X-Ray Image Classification of Pneumonia Disease Using EfficientNet and InceptionV3
Pneumonia can be described as a disease caused via viruses, bacteria, and fungi which lead to the inflammation of the lung and decreased oxygen absorption from air. It is one of the leading causes of death globally, reaching up-to 100,000 deaths caused by it globally. It is historically been challenging to identify this illness just by looking at chest X-rays. This study aims to smoothen the process of efficiently and accurately detecting pneumonia using Image Recognition based deep learning algorithms. This chapter aims to solve this problem using novel machine learning frameworks involving the Efficient-Net and InceptionV3 algorithms to achieve this goal. Our proposed models have achieved an accuracy of 92.93% via the InceptionV3 model and 95.39% via the EfficientNet model.
|Journal||Deep Learning Applications in Image Analysis|
|Publisher||Springer Nature Singapore|