ABSTRACT
This chapter presents an introductory overview of computer vision and the architecture of convolutional neural networks (CNN). It covers the basic functions of layers in deep learning, such as input, convolutional, non-linearity, pooling, fully connected, and output layers. The chapter also presents various applications of CNNs in tasks such as image classification, object detection, and image segmentation to highlight the versatility of this network. The basic concepts covered in this chapter relate to Case Study I of Chapter 6, which demonstrates the image classification problem.
