Hybrid Reverse Propagation ANN Adaptive Algorithm Based Deep Learning Image Processing for Pneumonia Detection

Authors

  • A.M. Prasanna Kumar Professor, Department of Electronics & Communication Engineering, ACS College of Engineering, Bengaluru, Karnataka, India
  • Vijaya S.M Associate Professor, Department of Electronics & Communication Engineering, Rajarajeswari College of Engineering, Bengaluru, Karnataka, India
  • Bharathi G Associate Professor, Department of Electronics & Communication Engineering, ACS College of Engineering, Bengaluru, Karnataka, India

Keywords:

Pneumonia, Transfer learning, Vgg19, Deep learning, Webpage

Abstract

Pneumonia is a syndrome that is caused by bacterial lung disease. This disease is diagnosed using a chest X-ray. Early diagnosis is important for successful treatment. This disease can be diagnosed using X-rays. Sometimes it can be confused with another bacterial disease due to an unclear chest X-ray. Consequently, we need a computer-aided diagnostic system to guide doctors. In this, amalgam backhaul algorithms are introduced to achieve multilayer network erudition. System noise investigation is done using artificial neural network (ANN). The vgg19 convolution neural network model was used to create a user-friendly website for the diagnosis of this disease. Simulated artificial neural network hybrid adaptive backpropagation algorithm used for deep learning image processing method in our training phase. The test results for the vgg19 network are with an accuracy of 0.91.

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Published

2022-09-01

Issue

Section

Articles