Real Time 2D Convolution and Max Pooling Process

In Convolutional Neural Network (CNN) consists of process of 2D convolution and max pooling.2D convolution is performed to express the shape of an object in an image.Max pooling is one way to reduce the spatial dimensions of an input volume.They are together to create an object's feature.As we know, the feature extraction is an important part in classification and detection task.A good feature can distinguish the shape of one object from another.It will increase the classification and detection accuracy.In this paper, researcher will build and observe the real time 2-D convolution and max pooling process for feature extraction.