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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| Main Authors: | Joseph Otoo, Suleman Nasiru, Irene Dekomwine Angbing |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827025000349 |
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