Recognition and classification of mathematical expressions using machine learning and deep learning methods

The advent of various machine learning methods can add a distinct dimension to the domain of recognition. The realm of pattern recognition has been deeply influenced by the ongoing trend of artificial learning-based methodologies. The two-dimensional structure of mathematical symbols and expressions makes recognition tasks more difficult, particularly for mathematical expressions. This paper delves into recognition approaches based on machine learning and deep learning. The leading recognition algorithms from both categories, SVM, and CNN, have been deployed to recognize the Hasyv2 dataset. The competent accuracies of 62.3% and 76.21% have been given by SVM and CNN, respectively.