Introduction to Convolution Process of CNN | Great Learning

Convolutional Neural Network (CNN) is a type of Deep Neural Network which is majorly used in applications related to Computer Vision such as image classification, image recognition and object detection etc. In general, the Convolution process yields a new function by merging two functions. In CNN specifically, the process of convolution takes place on the input data with the help of filters which produces a feature map.

In this session, we will talk about Digital image, the feature of digital images, the Convolution process to locate features of image and pooling features such as max and average pooling. We will understand in detail about light wells, pixels, image as numerical grid and function, image features such as pixel gradient as edges etc. We will also uncover kernels and various filters along with feature maps in the Convolution process of CNN.

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