An Efficient Dropout for Robust Deep Neural Networks
Overfitting remains a major difficulty in training deep neural networks, especially when attempting to achieve good generalization in complex classification tasks. Standard dropout is often employed to address this issue; however, its uniform random inactivation of neurons typically leads to instabi...
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| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2025-07-01
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| coleção: | Applied Sciences |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/2076-3417/15/15/8301 |
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