**3. Computer vision with neural networks**

Computer vision (CV) and AI research have several decades of steady progress. Specifically, the part of this discipline that uses convolutional neural networks (CNN) for image processing had its first boom with handwritten digit identification in 1989. This application was developed by Yann LeCun using some of the insights previously proposed by Kunihiko Fukushima [5]. Since computational capabilities at that time were scarce, there was little research in this area between 1990 and 2000. Thanks to the progressive increase in processing and storage capacities, in 2012 the AlexNet model was tested in competition with great success and from then on, the field of computer vision began to be populated with numerous applications [7]. The applications varied according to the type of task required and the type of dataset used. Also at this time, several authors began to investigate further the structure of the different published models and started to work on their taxonomy. Thus, we have articles that examined the components of various CNNs and their interconnection [8] and others that analyzed the different architectures, their engineering challenges, and their possible future applications [4, 9].
