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Prairie Dog Optimization Algorithm with deep learning assisted based Aerial Image Classification on UAV imagery

Year: 2024
Type: article
Abstract: This study presents a Prairie Dog Optimization Algorithm with a Deep learning-assisted Aerial Image Classification Approach (PDODL-AICA) on UAV images. The PDODL-AICA technique exploits the optimal DL model for classifying aerial images into numerous classes. In the presented PDODL-AICA technique, the feature extraction procedure is executed using the EfficientNetB7 model. Besides, the hyperparameter tuning of the EfficientNetB7 technique uses the PDO model. The PDODL-AICA technique uses a convolutional variational autoencoder (CVAE) model to detect and classify aerial images. The performance study of the PDODL-AICA model is implemented on a benchmark UAV image dataset. The experimental values inferred the authority of the PDODL-AICA approach over recent models in terms of dissimilar measures.
Source: Heliyon
DOI: 10.1016/j.heliyon.2024.e37446
Authors: Amal K. Alkhalifa, Muhammad Kashif Saeed, Kamal M. Othman, Shouki A. Ebad, Mohammed Alonazi, Abdullah Mohamed
Institutions: Princess Nourah bint Abdulrahman University, King Khalid University, Umm al-Qura University, Northern Border University, Prince Sattam Bin Abdulaziz University, Future University in Egypt
Language: English
Open Access status: gold
Estimated APC paid: $2,100
OpenAlex ID: W4402328411
FWCI: 0.503
Cites: 24
Cited by: 3
Related to: 10