DOODLECALC: A REAL-TIME HANDWRITTEN LINEAR ALGEBRA SOLVER USING DEEP LEARNING

Abstract

In educational technology, innovative tools that enhance student engagement and learning efficiency are crucial. This innovative project proposes the development of a Doodle-Based Handwritten Linear Algebraic Math Recognizer and Solver, an approach to solving linear algebraic problems through interactive doodling. Utilizing advanced image processing and deep learning techniques to achieve accurate recognition and solving capabilities, the core objective is to create a system that allows users to draw linear algebraic expressions and equations directly, which are then recognized, parsed, and solved in real-time. Key components of the project include real-time feedback mechanisms to assist users as they draw, and a robust parsing engine that translates doodle sequences into structured algebraic formulas. By integrating educational technology with interactive doodling, this project seeks to offer innovative strategies that supports and enhance the learning experience in linear algebra and broaden the accessibility of mathematical computations. DoodleCalc is designed to revolutionize mathematical problem-solving by offering an intuitive and interactive platform accessible to users of all levels with its user-friendly interface and real-time feedback.