Hyper-Tuned CNN Using EVO Technique for Efficient Biomedical Image Classification

Hyper-Tuned CNN Using EVO Technique for Efficient Biomedical Image Classification

This research utilizes metaheuristic optimization inspired by the Egyptian Vulture Optimization (EVO) technique. Biomedical image segregation is developed to reduce the complex association of hyperparameters of Convolutional Neural networks (CNN). The complex attributes of CNN include the type of ke...

Full description

Bibliographic Details
Main Authors: Abu Al-Haija, Q. (Author), Alnabhan, M. (Author), Habboush, A.K (Author), Mohanty, A.K (Author), Pattanayak, B.K (Author), Pattnaik, S. (Author)
Format: Article
Language:English
Published: Hindawi Limited 2022
Subjects:
Biomedical images
Classification (of information)
Complex networks
Convolution
Convolutional neural network
Convolutional neural networks
Deep learning
Egyptian vulture
Hyper-parameter
Image classification
Images classification
Kernel size
Life cycle
Magnetic resonance imaging
Metaheuristic optimization
Network-based
Optimization
Optimization models
Optimization techniques
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items