Artificial Intelligence-Based Optimization Algorithm to Recognize the Handwritten Digits of Writers

Abstract

The proliferation of technology has been credited with making processes that used to take a lot of time more easier to do. Machine learning (ML) enables software products to grow increasingly accurate at predicting outcomes without the need to be explicitly programmed to do so. This is possible because ML allows software to learn from past experiences. Machine learning algorithms make predictions about future output values by using data from the past as input. In the course of this investigation, we are going to investigate an artificial intelligence (AI)-based optimization method with the goal of recognizing the digits that are written by hand. Research in the fields of machine learning, image processing, and computer vision are making significant progress in the area of handwritten digit recognition. The style, shape, orientation, and size of a digit written by one person may be different from those written by another person. An algorithm for optimization is a procedure that repeatedly evaluates a number of potential solutions in order to locate the one that is most suitable. The phase of the design process known as computer-aided design has always included optimization ever since computers were first developed.