Chapter Objectives
• To know the limitations of traditional neural networks for image recognition.
• To understand the working principles of convolutional neural network (CNN).
• To understand the architecture of CNN.
• To know the importance of convolution layer, max pooling, flattening, and full connection layer of CNN model.
• To understand the process of training a CNN model.
• To decide the optimal number of epochs to train a neural network.
18.1 Image Recognition
Using a convolutional neural network (CNN), technological development in image recognition has revolutionized far beyond our imagination. Let us consider the comic scene shown in Figure 18.1, as it provides interesting insights into the development of image recognition and depicts a decade-back possible scenario. Here, a manager asks his computer programmer to “Develop an app which can check whether the user is in a national park or not, when he clicks some photo!” Being an easy and feasible task, the computer programmer responds that the task is merely of few hours. But, the manager's curiosity goes up, and he asks the programmer further to check whether the image is of a bird or not? Surprisingly, the programmer responds, “I need a research team and five years for this task.”
This surprised the manager as he expected it to be an easy task. But the programmer who has a knack in the field knows that it is one of the complex problems to be addressed in computer science.
In the last decade, we have provided solutions to many complex problems in the field of computers. But, for the last 50 years, we have been struggling to solve the problems in image recognition. However, thanks to the efforts of researchers and computer scientists across the globe, we can solve these problems now. Even a three-year-old child can identify a bird's photo, but identifying a way by which computers can do the same task was not a cake-walk; hence, it took almost 50 years!
We have finally found a promising approach for object recognition using deep CNN in recent years. In this chapter, we will discuss the working principle and concepts of CNN, a deep neural network approach to solving the problem of image recognition.
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