What are the uses of pooling layers in CNN

Pooling Layer The main purpose of pooling layer is to progressively reduce the spatial size of the input image, so that number of computations in the network are reduced. Pooling performs downsampling by reducing the size and sends only the important data to next layers in CNN.

References: 

https://www.researchgate.net/figure/Figurec-convolution-operation-B-Pooling-Layer-The-main-purpose-of-pooling-layer-is-to_fig2_332570921#:~:text=Pooling%20Layer%20The%20main%20purpose%20of%20pooling%20layer%20is%20to,to%20next%20layers%20in%20CNN.