Shifted Hexpo activation function: An improved vanishing gradient mitigation activation function for disease classification

Shifted Hexpo activation function: An improved vanishing gradient mitigation activation function for disease classification

Activation functions (AFs) in deep learning significantly impacts model performance. In this study, we proposed Shifted Hexpo (SHexpo), an improved variant of the Hexpo AF, designed to address limitations such as vanishing gradients and parameter sensitivity. SHexpo introduces a shifting parameter,...

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Bibliographic Details
Main Authors: Joseph Otoo, Suleman Nasiru, Irene Dekomwine Angbing
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Machine Learning with Applications
Subjects:
Convolutional neural network
Activation function
Cervical cancer
Hexpo
Deep learning
Medical image classifications
Online Access:http://www.sciencedirect.com/science/article/pii/S2666827025000349
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