Uses VGG16 model to predict Covid19 from chest XRay images

VGG-16 architecture model applied on a chest xray dataset from kaggle.

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Classification of chest xray images into two categories using VGG16.

Using chest xray images to detect pneumonia. This is a follow through case study using VGG16 CNN

Pneumonia Detection with Chest X-Ray images.Image classification built on top of VGG16 pre-trained model using Tenserflow and Keras. I have collected this dataset from kaggle "https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia".

Here we have used Deep learning models VGG16 and Inception V3 to do the classification of two datasets (Birds Species and Chest Xrays to classify Pneumonia) . A comparison between the two models is also done

Computational flu or COVID-19 anticipator and prescriber. Dataset link :- https://www.kaggle.com/bachrr/covid-chest-xray. We created a deep learning model based on VGG16 architecture to make a classifier that classifies chest Xrays into two categories (COVID positive and COVID negative). Then Used the outcome of the classifier to Prescribe CDSCO certified drugs which are widely available in the Indian market.

This is a thesis project done with using reznet50, vgg16 and alexnet models with TensorFlow and Pytorch. We are training them with over 1600 images of covid and normal Chest Xrays. Dataset from : https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database