Original article was published by Krishna on Artificial Intelligence on Medium
COVID -19 Detector with VGG-19 Convolutional Neural Network
Know your lungs to attest of COVID!!! (A compact real world deep learning project for beginners.)
COVID-19 Detector is a web application that solves some part of the current problem faced by the world of pandemic COVID -19 virus. It helps users like doctors for checking their lungs X-ray images. For this, they need to upload the photocopy or an image of the X-ray and the web application, and they will get the result where there is COVID-19 effect still exists in the lungs or not. It will also help to predict when the person has chances of having coronavirus.
The necessary library for this project are:
What is VGG-19 Convolutional Neural Network?
Convolutional Neural Networks are specific deep neural networks that can process data with an input shape like a 2D matrix. Images are commonly represented as a 2D matrix, and CNN is beneficial when working with images. It scans images from top to bottom and left to right to extract essential features from the image and combine the extracted features to identify the images. It can manage images that have been translated, rotated, scaled, and change in perspective.
For this particular project, VGG -19, a type of CNN model is used, which is 19 weight layers consisting of 16 convolutional layers with 3 fully connected layers and the same 5 pooling layers.
The input is a 224 * 224 RGB image to VGG based convNet. The pre-processing layer takes the RGB image with pixel values in the range 0–255 and subtracts the mean image values computed over the entire ImageNet training collection. After pre-processing, the input images are passed through layers of weight. The training images are processed through a stack of convolutional layers.
The architecture of VGG-19: