Fusing batch normalization and convolution

[HKLee2040]

In many previous works, they show that it's more difficult to do quantization while the batch normalization is fused with convolution due to wider variance of weight range.
So, do you have any comment about quantizing the model with fused batch normalization and convolution if only smarter min/max value range of activation quantization is set?