• Sagar Shinde
• Lalit kumar Wadhwa

Every day, the expressions and symbols used in mathematical calculations are prominent and used in a routine manner. To effectively access these documents, they should be digitized and produced in electronic formats. The goal of this review is to bridge the gap between the knowledge that people have about math and the input that they are receiving from the organizers. In addition to the printed documents, handwritten notes and symbols could also be digitized and used to introduce math notation to electronic devices. In addition to the printed documents, handwritten notes and symbols could also be digitized and used to introduce math notation to electronic devices. This review proposes a method that combines the capabilities of a static and complex feature extraction system with a nearest neighbor classifier, support vector machine, back propagation neural network etc. The survey is focused on developing a method to recognize mathematical equations and symbols too.

Math equations & symbols, Recognition, Support vector machine, Neural network, Nearest neighbor .

"RECOGNITION OF HANDWRITTEN MATHEMATICAL EQUATIONS: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.267-271, June-2019, Available :http://www.jetir.org/papers/JETIR1908E36.pdf

"RECOGNITION OF HANDWRITTEN MATHEMATICAL EQUATIONS: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp267-271, June-2019, Available at : http://www.jetir.org/papers/JETIR1908E36.pdf