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Enhancing deep neural network training through learnable adaptive normalization

delete2025-07-05
delete0
PRE
AI
J
Jan Benedikt Ruhland
I
Iraj Masoudian
D
Dominik Heider
DOI：10.1016/j.knosys.2025.113968delete
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摘要

摘要

En 中文
归一化是数据科学中一种基本的预处理技术，通常用于在模型训练前标准化数据分布。其主要作用是保持特征之间一致的统计特性，这有助于实现高效学习并增强训练稳定性。在深度学习中，归一化方法尤其有益，因为它们能够调节神经网络中的输入分布，促进更稳定的训练和更快的收敛。
Keyword:
Artificial intelligence
Machine learning
Deep learning
AI in Medicine

期刊

K
Knowledge-Based Systems
IF:
7.6
论文数:
1.2W
被引数:
4.5W

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暂无机构信息
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