Adaptive hybrid hyperparameter optimization with MRFO and Lévy flight for accurate melanoma classification

Adaptive hybrid hyperparameter optimization with MRFO and Lévy flight for accurate melanoma classification

Abstract Hyperparameter optimization (HPO) is essential for deep learning in medical image classification, yet standard metaheuristics such as Manta Ray Foraging Optimization (MRFO) often suffer from premature convergence in high-dimensional search spaces. To address these limitations, an enhanced v...

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Bibliographic Details
Main Authors: Shamsuddeen Adamu, Hitham Alhussian, Said Jadid Abdulkadir, Ayed Alwadin, Sallam O. F. Khairy, Hussaini Mamman, Shamsu Abdullahi, Saidu Yahaya, Aliyu Garba, Dahiru Adamu Aliyu, Muhammad Muntasir Yakubu, Daniel Tonye Oyefidein
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Journal of King Saud University: Computer and Information Sciences
Subjects:
Melanoma classification
Hyperparameter optimization
MRFO-LF
Deep learning
Medical imaging
Online Access:https://doi.org/10.1007/s44443-025-00078-3
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