A Comparative Study of Deep Learning Networks for COVID-19 Recognition in Chest X-ray Images

A Comparative Study of Deep Learning Networks for COVID-19 Recognition in Chest X-ray Images

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Product Code: Python - Deep Learning
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Product Description

Aim:

       To detect the COVID-19 using x-ray images by using Convolutional neural network.

Abstract:

           The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world and became a plague. Due to the regular increase in cases, the number of COVID-19 test kits available in the hospital is minimal. Since an automated detection system is needed as an alternative diagnosis to prevent COVID-19 from spreading among people. It is necessary to detect the positive cases as early as possible so as to prevent the further spread of this disease. Application of Convolutional neural networks (CNN) techniques coupled with medical imaging can be helpful for the accurate detection of this disease. In this project a new model for automated COVID-19 detection using raw chest X-ray images is used. The model is developed to supply accurate diagnosis for binary classification (COVID vs. No-Findings). We introduced Convolutional layers and implemented different filtering on each layer.

 

Proposed System:

          The Covid-19 pandemic has consumed the world, with 192 countries affected and global cases nearing 150 million. To overcome the fallback in the existing system we propose a Deep learning based system to increase the speed and accuracy. We have proposed an automatic prediction of Covid-19 using a Convolutional neural networks and Chest X-ray images. Chest X-ray is the best tool for the detection of covid-19.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.