Comprehensive Guide to Different Pooling Layers in Deep Learning
Pooling layers: basic work of the pooling layer is to downsample the feature map. Fully connected layer: this is a conventional feed-forward neural network. Which consists of an activation function in order to make predictions.
Pooling layers: basic work of the pooling layer is to downsample the feature map. Fully connected layer: this is a conventional feed-forward neural network. Which consists of an activation function in order to make predictions.
predictions, order, activation function, feature map, basic work, pooling layer, Fully connected layer, conventional feed-forward neural network
