Abstract
This chapter introduces the convolutional neural networks (CNNs, or ConvNets for short), deep neural networks with special image processing applications. These networks significantly improve the processing of information by providing several new concepts, and are still a great option in many problems involving continuously sampled data in a rectangular grid: audio signals (1D), images (2D), volumetric MRI data (3D), and more. A ConvNet is an old method developed in the 1980s and 1990s. It was relatively long forgotten because it was impractical in real applications of complex images. Since 2012 this method has received considerable attention again and has been used in most computer vision studies. Therefore, it has been evolving rapidly. After introducing the basics of convolutional networks, this chapter analyzes three applications of convolutional neural networks in bioinformatics, namely coronavirus disease (COVID-19) diagnosis, breast cancer predicting, and diabetic retinopathy detection.
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