Handwritten equation solver using Convolutional Neural Network
Mitali Arya, Pavinder Yadav, Nidhi Gupta · 2023
Because of the ongoing Covid-19 pandemic, educational activities resulted in an unanticipated change from traditional learning to a digital teaching and learning environment. E-learning is the delivery of educational content and learning via digital resources. It increases the digitization of handwritten documents because students are required to submit their homework and assignments online. This work proposes an automatic system for handwritten numeric recognition and equation solver based on Convolutional Neural Network to assist teachers and parents in checking handwritten assignments. Handwritten digit recognition refers to the ability of the computer machine to recognize handwritten digits from various sources, such as published researches, real-world images, touch display, and so on. In this work, the CNN model is used to recognize and solve handwritten equations that contain four basic arithmetical operations – addition, subtraction, division and multiplication. The handwritten linear equations with some limitations are also being solved by the proposed model.