AMSFMap Methodology to improve prediction accuracy of CNN model for Covid19 using X-ray images

Author:

Chauhan Hetal,Modi Kirit

Publisher

Elsevier BV

Subject

General Engineering

Reference20 articles.

1. White paper report of the RAD-AID Conference on International Radiology for Developing Countries: identifying challenges, opportunities, and strategies for imaging services in the developing world;Mollura;Journal of the American College of Radiology,2010

2. RAD-AID conference on international radiology for developing countries: the evolving global radiology landscape;Kesselman;Journal of the American College of Radiology,2016

3. Precise prediction of COVID-19 in chest X-Ray images using KE sieve algorithm;Thejeshwar;MedRxiv,2020

4. Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks;Narin;Pattern Analysis and Applications,2021

5. Predicting covid-19 pneumonia severity on chest x-ray with deep learning;Cohen;Cureus,2020

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1. Synergistic Fusion of U-Net and DeepLabV3+ for Enhanced Lung Disease Segmentation: A Comprehensive Evaluation and Performance Analysis;2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT);2024-02-09

2. A Deep Learning Framework for COVID-19 Detection in X-Ray Images with Global Thresholding;2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN);2023-05-05

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