BatchNormalization layer - Keras Layer that normalizes its inputs Batch normalization applies a transformation that maintains the mean output close to 0 and the output standard deviation close to 1 Importantly, batch normalization works differently during training and during inference
tf. keras. layers. BatchNormalization | TensorFlow v2. 16. 1 Importantly, batch normalization works differently during training and during inference During training (i e when using fit() or when calling the layer model with the argument training=True), the layer normalizes its output using the mean and standard deviation of the current batch of inputs
BatchNormalizationLayer - Batch normalization layer - MATLAB To speed up training of the convolutional neural network and reduce the sensitivity to network initialization, use batch normalization layers between convolutional layers and nonlinearities, such as ReLU layers