Pooling Layers in CNN
Pooling Layers in Convolutional Neural Networks (CNNs) are layers that reduce the spatial dimensions of feature maps while retaining important information learned by convolutional layers.
Common use cases
Pooling layers are commonly used in image classification, object detection, image recognition, facial recognition, medical imaging, and other computer vision applications.