Is your proposal related to a problem? Please describe.
Description :- The Coronavirus Disease 2019 (COVID-19) has brought a worldwide threat to the living society. The whole world was 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.
Aim :- 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.
Solution I propose :-
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 @Kushal997-das and lable it as level-3 if possible 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 > I will also be doing EDA analysis for the dataset.
I want to add this project in advance ml/data science repo
Add any other context or screenshots about the proposal request here.
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Thanks for opening thisIssue 🙌, Welcome to Project Guidance 💖 We will review everything and get back to you. Make sure to give a star to this repo before making a fork! Thank you :)
Is your proposal related to a problem? Please describe.
Description :- The Coronavirus Disease 2019 (COVID-19) has brought a worldwide threat to the living society. The whole world was 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.
Aim :- 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 I'll use :- https://www.kaggle.com/datasets/pranavraikokte/covid19-image-dataset
Solution I propose :- 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 @Kushal997-das and lable it as level-3 if possible 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 > I will also be doing EDA analysis for the dataset.
I want to add this project in advance ml/data science repo
Add any other context or screenshots about the proposal request here.
No response