Early Prediction of COVID-19 Suspects Based on Fractional Order Optical Flow
Author:
Affiliation:
1. Maulana Azad National Institute of Technology,Department of Mathematics, Bioinformatics and Computer Applications,Bhopal,India,462003
Funder
SERB
MHRD
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9702150/9702296/09702356.pdf?arnumber=9702356
Reference21 articles.
1. COVID-19 Control by Computer Vision Approaches: A Survey
2. Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks;narin;ArXiv Preprint,2020
3. Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network
4. A fractional order variational model for the robust estimation of optical flow from image sequences
5. Fractional variational optical flow model for motion estimation;sheng;International Federation of Automatic Control,2010
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1. Caputo derivative based nonlinear fractional order variational model for motion estimation in various application oriented spectrum;Sādhanā;2023-12-22
2. Study of Various Deep Learning Models for COVID-19 Detection Based on Fractional Order Optical Flow;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06
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