[Project Addition] : Covid-19 X-Ray Image Classification

[aaradhyasinghgaur]

Is your feature request related to a problem? Please describe.
The Coronavirus Disease 2019 (COVID-19) has brought a worldwide threat to the living society. The whole world is putting incredible efforts to fight against the spread of this deadly disease. Meanwhile, hundreds of machine-learning experts volunteer their time and expertise to help medical researchers in this fight.

One of the areas where machine learning can help is detecting the COVID-19 cases from chest X-ray images. The task is a simple classification problem where given an input chest X-ray image, the machine learning-based model must detect whether the subject of study has been infected or not.

Dataset :- https://www.kaggle.com/datasets/pranavraikokte/covid19-image-dataset

Describe the solution you'd like

1. ) Using 5 different available network architectures such as Xception , DenseNet121 , VGG16 etc. to do catagorical classification for chest X-ray to detect COVID19 symptoms .
   2.) use data augmentation techniques to improve the accuarcy of models.
   3.) Comparing performance and accuracy of models using accuracy score ,loss and accuracy graph , confusion matrix for better understanding.
   4.) Perfroming EDA (data analysis) for dataset to understand the structure of data.
   5.) Using README file for describing the work I've performed.

Kindly assign this issue to me @TAHIR0110 and lable it as level-3 as I'm training and testing dataset for 5 different models which is resource and time consuming and also making doucumentation about which works better.

[TAHIR0110]

@kyra-09 assigned!

[TanviPoddar]

I would love to work on this too as I have prior experience in deep learning.