Introduction: Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that have revolutionized the field of computer vision. They are specifically designed to process image data and have been widely adopted in applications such as image classification, object detection, and image segmentation. In this blog, we will delve into the workings of a CNN and understand its key components. The Key Components of a CNN A CNN is made up of multiple layers including convolutional layers, activation layers, pooling layers, and fully connected layers. Let's take a closer look at each of these components: Convolutional Layer: The convolutional layer is the heart of a CNN and is responsible for performing the convolution operation on the input image. The convolution operation involves applying a set of filters to the input image to extract important features. These filters can be thought of as small matrices that are multiplied with small regions of the image to produce a new ...