Enhancing Red Palm Weevil Detection Using Bird Swarm Algorithm With Deep Learning Model-Reference-Cited by-同舟云学术

Enhancing Red Palm Weevil Detection Using Bird Swarm Algorithm With Deep Learning Model

Published:2024 Issue: Volume:12 Page:1542-1551
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Arasi Munya A.¹^ORCID,Almuqren Latifah²^ORCID,Issaoui Imène³,Almalki Nabil Sharaf⁴,Mahmud Ahmed⁵,Assiri Mohammed⁶^ORCID

Affiliation:

1. Department of Computer Science, College of Science and Arts in Rijal Almaa, King Khalid University, Abha, Saudi Arabia

2. Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia

3. Unit of Scientific Research, Applied College, Qassim University, Buraydah, Saudi Arabia

4. Department of Special Education, College of Education, King Saud University, Riyadh, Saudi Arabia

5. Research Center, Future University in Egypt, New Cairo, Egypt

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

Funder

Deanship of Scientific Research at King Khalid University

Princess Nourah bint Abdulrahman University Researchers

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Prince Sattam bin Abdulaziz University project

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

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10376148.pdf?arnumber=10376148

Reference27 articles.

1. Enhancing Accuracy of Yellowing Disease Severity Level Detection in Coconut Palms with SVM Regularization and CNN Feature Extraction

2. Developing Date Palm Tree Inventory from Satellite Remote Sensed Imagery using Deep Learning

3. Classifying Infected Palms with Dubas's Bug Based on Artificial Intelligence

4. Improved Power Normalized Cepstrum Coefficient Based on Wavelet Packet Decomposition for Trunk Borer Detection in Harsh Acoustic Environment

5. Agriculture 4.0 from IoT, Artificial Intelligence, Drone, & Blockchain Perspectives