Quantum-Inspired Moth Flame Optimizer Enhanced Deep Learning for Automated Rice Variety Classification-Reference-Cited by-同舟云学术

Quantum-Inspired Moth Flame Optimizer Enhanced Deep Learning for Automated Rice Variety Classification

Author:

Alshahrani Haya Mesfer¹,Saeed Muhammad Kashif²^ORCID,Alotaibi Saud S.³^ORCID,Mohamed Abdullah⁴,Assiri Mohammed⁵^ORCID,Ibrahim Sara Saadeldeen⁶

Affiliation:

1. Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

2. Department of Computer Science, Applied College at Muhayil, King Khalid University, Abha, Saudi Arabia

3. Department of Information Systems, College of Computing and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia

4. Research Centre, Future University in Egypt, New Cairo, Egypt

5. Department of Computer Science, College of Sciences and Humanities-Aflaj, Prince Sattam bin Abdulaziz University, Aflaj, Saudi Arabia

6. Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia

Funder

Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project

Princess Nourah bint Abdulrahman University Researchers

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Prince Sattam bin Abdulaziz University

Future University in Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference25 articles.

2. Classification of rice varieties using convolution neural network;sethi;Proc Int Interdiscipl Conf Math Eng Sci (MESIICON),2022

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