An Optimized Data and Model Centric Approach for Multi-Class Automated Urine Sediment Classification

Author:

Akhtar Sania1,Hanif Muhammad2ORCID,Rashid Ahmar1ORCID,Aurangzeb Khursheed3ORCID,Khan Ejaz Ahmad4ORCID,Saraoglu Hamdi Melih5,Javed Kamran6

Affiliation:

1. Faculty of Computer Science and Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan

2. Kobayashi Research Laboratory, Information Technology Center, The University of Tokyo, Tokyo, Japan

3. Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

4. Department of Public Health, Health Services Academy, Islamabad, Pakistan

5. Department of Electrical and Electronics, Kütahya Dumlupınar University, Kutahya, Turkey

6. National Centre of Artificial Intelligence (NCAI), Saudi Data and Artificial Intelligence Authority (SDAIA), Riyadh, Saudi Arabia

Funder

Researchers Supporting Project, King Saud University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

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