Given the ubiquity of handwriting and mathematical content in human transactions, machine
recognition of handwritten mathematical text and symbols has become a domain of great …

Automatic recognition of mathematical expressions is a challenging pattern recognition
problem since there are many ambiguities at different levels. On the one hand, the …

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

Long short-term memory networks (LSTM) achieve great success in temporal dependency
modeling for chain-structured data, such as texts and speeches. An extension toward more …

A system for recognizing online handwritten mathematical expressions (MEs), by applying
improved structural analysis, is proposed and experimentally evaluated on two databases …

We present an approach for on-line recognition of handwritten math symbols using
adaptations of off-line features and synthetic data generation. We compare the performance …

This paper presents application of deep learning to recognize online handwritten
mathematical symbols. Recently various deep learning architectures such as Convolution …

In mathematical expression recognition, symbol classification is a crucial step. Numerous
approaches for recognizing handwritten math symbols have been published, but most of …

This paper presents deep learning to recognize online handwritten mathematical symbols.
Recently various deep learning architectures such as Convolution neural networks (CNNs) …

Math plays a crucial role in each and every sector belonging to human beings in society.
Sometimes, it is verydifficult to recognize math equations & symbols due to variation in …