System for coronavirus classification based on a new textural descriptor-Reference-Cited by-同舟云学术

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System for coronavirus classification based on a new textural descriptor

Published:2022-12-19 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 21st international Ccnference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)
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Author:

Boubakri Fathia,Gargouri Norhene¹,Masmoudi Alima Damak²

Affiliation:

1. Digital Research Center of Sfax, Technopole of Sfax, Computer Imaging and Electronic System Group

2. Sfax Engineering School, University of Sfax,Computer Imaging and Electronic System Group,CEM Laboratory Department of Electrical Engineering,Sfax,Tunisia,3038

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10018923/10018970/10019167.pdf?arnumber=10019167

Reference19 articles.

1. Monogenic-LBP: A new approach for rotation invariant texture classification

2. A comparative study of texture measures with classification based on featured distributions

3. The monogenic signal

4. LBPV descriptors-based automatic ACR/BIRADS classification approach

5. SARS-Net: COVID-19 detection from chest x-rays by combining graph convolutional network and convolutional neural network

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Classification of Covid-19 Chest X-Ray Patients using Artificial Neural Network;2023 10th International Conference on Future Internet of Things and Cloud (FiCloud);2023-08-14

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