Project title
Classification of COVID-19 chest X-ray images using Convolutional Neural Networks (CNN)
Submitted to:
- Mr. Tejalal Choudhary
Submitted By:
- Piyush
- Suyash
- Mehak
- Savita
- Sumanth
Project Description
Currency is an indispensable part of our daily life. In this paper we have introduced a web application and a mobile application for currency recognition that recognises Indian currency in different views on scale. For this we have deployed a web application & android application as well to make it usable for the end user. The model which we worked on basically classifies the currency note into 1000/100/20/10/50/500 denominations.
Project Poster
Submitted to:
- Mr. Tejalal Choudhary
Submitted By:
- Aditi Godbole
- Aditya Babar
- Aditya Gurnani
- Aditi Verma
- Vaibhav Gattyani
Project Description
In this project, we take Chest X-ray images as the input and a CNN model is implemented on it to obtain the result as infected or normal. Various pre-trained models and a basic CNN model were implemented on the dataset which consisted of 689 images. It was concluded that CNN model gave the best accuracy after image augmentation and training over 35 epochs at a learning rate of 1e-4 for Adam optimizer. The testing accuracy that was obtained after pruning was 96.37%
Project Poster
