SURVEY OF NEURAL NETWORKS AND STANDARD IMAGE PROCESSING ALGORITHMS IN THE FIELD OF COMPUTER VISION

This research focuses on the important issue of comparing standard computer vision algorithms with neural networks. Standard algorithms based on traditional methods of image processing and computer vision have long been widely used in various industries. On the other hand, neural networks, inspired by the structure of the human brain, have undergone rapid development and have become a major tool in deep learning, big data analysis, and image processing. The question this article poses is how to choose the optimal approach to solving computer vision problems. Standard methods, with their classical and proven solutions, or neural networks, which demonstrate an impressive ability to automatically learn complex dependencies in data. The purpose of this article is to consider this issue from different angles, analysing the advantages and limitations of both approaches.