Improved Malaria Cells Detection Using Deep Convolutional Neural Network-Reference-Cited by-同舟云学术

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Improved Malaria Cells Detection Using Deep Convolutional Neural Network

Published:2023-06-08 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)
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Author:

Mahmood Sarmad Nozad¹,Mohammed Swash Sami¹,Ismaeel Ayad Ghany²,Clarke Hülya Gükalp³,Mahmood Iman Nozad⁴,Aziz Dlnya Abdulahad²,Alani Sameer⁵

Affiliation:

1. Electronic and Control Engineering Techniques Technical Engineering College, Northern Technical University,Kirkuk,Iraq

2. Computer Technology Engineering College of Engineering Technology, Al-Kitab University,Kirkuk,Iraq

3. Electrical and Electronics Engineering Ondokuz Mayıs University,Samsun,Turkey

4. Kirkuk General Education Directorate,Kirkuk,Iraq

5. Computer Center, University of Anbar,Anbar,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10156655/10155769/10156747.pdf?arnumber=10156747

Reference13 articles.

1. Malaria Cell Images Dataset;Kaggle,2015

2. Computer-Aided Diagnosis System for Blood Diseases Using EfficientNet-B3 Based on a Dynamic Learning Algorithm

3. Deep Malaria Parasite Detection in Thin Blood Smear Microscopic Images

4. A Novel Shallow ConvNet-18 for Malaria Parasite Detection in Thin Blood Smear Images

5. Exploring anti-corruption, transparency, and accountability in the World Health Organization, the United Nations Development Programme, the World Bank Group, and the Global Fund to Fight AIDS, Tuberculosis and Malaria

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