Ankush Tamta

Handwritten Equation Solver

 Our Handwritten Equation Solver project seeks to create an advanced system capable of accurately recognizing and solving handwritten mathematical equations from images. This innovative solution will cover a broad spectrum of mathematical expressions, including elementary arithmetic operations as well as equations of various degrees (e.g., linear, quadratic, cubic). Key components of this project will entail the application of cutting-edge technologies, such as Optical Character Recognition (OCR) for image preprocessing and character segmentation, coupled with Convolutional Neural Networks (CNN) for character prediction. This project holds promise for enhancing mathematics education and streamlining complex equation-solving tasks.

Hand Gesture Mouse Control

Our hand gesture-based mouse control project, built using machine learning and OpenCV, introduces a novel and intuitive way to interact with computers. Leveraging state-of-the-art computer vision techniques, we have developed a system that interprets hand gestures in real-time to control the mouse cursor. Users can perform a range of actions, including cursor movement, left and right-click functionality, and scrolling, all through natural hand movements. This project showcases the fusion of cutting-edge technology and human-computer interaction, making computing more accessible and interactive.