Translations:Batch Normalization/1/en

Batch normalization (often abbreviated BatchNorm or BN) is a technique for improving the speed, stability, and performance of deep neural networks by normalizing the inputs to each layer. Introduced by Ioffe and Szegedy in 2015, it has become a standard component in most modern deep learning architectures.