In deep learning, a ______________ layer is used to reduce the spatial dimensions of the input volume through subsampling.

Which layer in a CNN is responsible for reducing the spatial dimensions of the input data?a.Convolutional layerb.Activation layerc.Fully connected layerd.Pooling layer

In the discriminator's code, which layer helps in reducing the dimensions of the input image?DenseUpSampling2DBatchNormalizationConv2D with stridesReshape

In a convolutional neural network (CNN), what is the primary role of the pooling layer? Question 2 options: Reducing the number of parameters in the network. Introducing non-linearities into the network. Performing element-wise multiplication with the filter weights. Down-sampling the feature maps to reduce spatial dimensions.

In a Convolutional Neural Network, the operation helps detect spatial hierarchies in the input image.

A ______________ is a small matrix used in convolutional layers to detect patterns in the input data.