Flipover outperforms dropout in deep learning

Flipover outperforms dropout in deep learning

Abstract Flipover, an enhanced dropout technique, is introduced to improve the robustness of artificial neural networks. In contrast to dropout, which involves randomly removing certain neurons and their connections, flipover randomly selects neurons and reverts their outputs using a negative multip...

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Bibliographic Details
Main Authors: Yuxuan Liang, Chuang Niu, Pingkun Yan, Ge Wang
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Visual Computing for Industry, Biomedicine, and Art
Subjects:
Model robustness
Regularization
Flipover
Dropout
Adversarial defense
Online Access:https://doi.org/10.1186/s42492-024-00153-y

Internet

https://doi.org/10.1186/s42492-024-00153-y

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