Average Pooling calculates the average of the elements in a predefined sized Image section. In Max Pooling, the largest element is taken from feature map. Depending upon method used, there are several types of Pooling operations. This is performed by decreasing the connections between layers and independently operates on each feature map. The primary aim of this layer is to decrease the size of the convolved feature map to reduce the computational costs. In most cases, a Convolutional Layer is followed by a Pooling Layer. Later, this feature map is fed to other layers to learn several other features of the input image. The output is termed as the Feature map which gives us information about the image such as the corners and edges. By sliding the filter over the input image, the dot product is taken between the filter and the parts of the input image with respect to the size of the filter (MxM). In this layer, the mathematical operation of convolution is performed between the input image and a filter of a particular size MxM. This layer is the first layer that is used to extract the various features from the input images. In addition to these three layers, there are two more important parameters which are the dropout layer and the activation function which are defined below. When these layers are stacked, a CNN architecture will be formed. There are three types of layers that make up the CNN which are the convolutional layers, pooling layers, and fully-connected (FC) layers.
Deep learning, there are several types of models such as the Artificial Neural Networks (ANN), Autoencoders, Recurrent Neural Networks (RNN) and Reinforcement Learning. It teaches the computer to do what naturally comes to humans. These structures are called as Neural Networks. Deep Learning a subset of Machine Learning which consists of algorithms that are inspired by the functioning of the human brain or the neural networks. In the last few years of the IT industry, there has been a huge demand for once particular skill set known as Deep Learning. What is the benefit of standard CNN architectures?.What are the basic components of the convolutional neural network architecture?.