Batch normalization is applied to individual layers. Select the wrong statement about batch normalization from the following options.

Question $6$ options:

After applying standardization, we apply a scale coefficient and offset.

In each training iteration, we first normalize the inputs of batch normalization by subtracting their mean and dividing by their standard deviation, where both are estimated based on the statistics of the current minibatch.

Batch normalization normalizes the output distribution to be more uniform across dimensions.

Batch normalization is a regularization technique that will add a penalizing term to the cost function.

Batch normalization restricts the activation functions from taking too high or low values and indirectly improves training time.