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It is shown that Batch Normalization is not only important in improving the performance of the neural networks, but are essential for being able to train a deep convolutional networks.
Consequently, it promises higher discrimination power for the batch-normalized mini-batch.
Open accessProceedings ArticleDOI
Lei Huang, Yi Zhou, Fan Zhu, Li Liu, Ling Shao 
01 Jun 2019
66 Citations
Decorrelated Batch Normalization (DBN) further boosts the above effectiveness by whitening.
To reduce memory and computational cost, we propose Stochastic Batch Normalization -- an efficient approximation of proper inference procedure.

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