CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 Diagnosis-Reference-Cited by-同舟云学术

CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 Diagnosis

Published:2022-10-09 Issue: Volume: Page:
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Container-title:2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
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Author:

Khanam Sadia¹,Qazani Mohammad Reza Chalak²,Mondal Subrota Kumar³,Kabir Hm Dipu²,Sabyasachi Abadhan S.³,Asadi Houshyar²,Kumar Keshav⁴,Tabarsinezhad Farzin⁵,Mohamed Shady²,Khorsavi Abbas²,Nahavandi Saeid²

Affiliation:

1. Dhaka Dental College,Dhaka,Bangladesh

2. Deakin University,Institute for Intelligent Systems Research and Innovation (IISRI),Australia

3. The Hong Kong University of Science and Technology,Hong Kong

4. University Institute of Computing, Chandigarh University,Punjab,India

5. University of Tehran,Iran

Funder

Australian Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9945068/9945069/09945615.pdf?arnumber=9945615

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3. SpinalXNet: Transfer Learning with Modified Fully Connected Layer for X-Ray Image Classification

4. CoV2-Detect-Net: Design of COVID-19 prediction model based on hybrid DE-PSO with SVM using chest X-ray images

5. COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images

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