Context: Many scientific and technical literature documents contain MSs and MEs that are
more challenging to be recognized by computers than plain text. The recognition of HMSE …

Tools based on machine learning (ML) have seen widespread application in the prediction
and categorization of mathematical symbols and phrases. The purpose of this work is to …

Handwritten mathematical expressions are an essential part of many domains, including
education, engineering, and science. The pervasive availability of computationally powerful …

With the advent and advancement of machine learning and deep learning techniques,
machine-based recognition systems for mathematical text have captivated the attention of …

An automatic system that helps teachers and students verify the correctness of handwritten
derivation in mathematics homework is proposed. The system acquires input image …

In this study, we propose a system that can recognize offline handwritten mathematical
expressions using limited training data. The purpose of the system is to exhibit a high …

Offline handwritten mathematical expression recognition (HMER) is a significant area in
mathematical expression recognition. However, offline HMER is often viewed as a much …

Recognition of handwritten mathematical expressions has been an important topic for many
researchers for decades. It remains one of the most challenging and exciting areas in …

Online handwritten mathematical expressions consist of sequences of strokes. Automatic
recognition these data requires solving three subproblems: symbol segmentation, symbol …

The field of mathematics is very important with its applications in every aspect of science in
general and engineering in particular. Mathematical expressions form a vital component of …