Revolutionizing Oral Cancer Detection: An Approach Using Aquila and Gorilla Algorithms Optimized Transfer Learning-Based CNNs

Revolutionizing Oral Cancer Detection: An Approach Using Aquila and Gorilla Algorithms Optimized Transfer Learning-Based CNNs

The early detection of oral cancer is pivotal for improving patient survival rates. However, the high cost of manual initial screenings poses a challenge, especially in resource-limited settings. Deep learning offers an enticing solution by enabling automated and cost-effective screening. This study...

Full description

Bibliographic Details
Main Authors: Mahmoud Badawy, Hossam Magdy Balaha, Ahmed S. Maklad, Abdulqader M. Almars, Mostafa A. Elhosseini
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Biomimetics
Subjects:
classification
convolutional neural network (CNN)
deep learning (DL)
Gorilla Troops Optimizer (GTO)
Online Access:https://www.mdpi.com/2313-7673/8/6/499

Similar Items

Similar Items