By superimposing double residuals in the Main Stage the networks expressiveness is further improved near the data input part capturing subtle features in the input data The model is made to circumvent

In simpler terms, by using double residuals in the Main Stage, the network can better understand and identify small details in the input data. This helps to reduce misclassifications and improve the overall accuracy of the model.