Engineered an AI model utilizing advanced Computer Vision and Google Generative AI to solve math problems by recognizing hand gestures, offering real-time, accurate solutions through an intuitive interface inspired by Apple Tablet calculators.

This project presents a deep learning-driven approach for hand gesture recognition in virtual museums using a combinaison of CNN and LSTM.

Naruto Hand Gesture Recognition with OpenCV and Transfer Learning

A Sign Language Learning Platform where who know sign language can come and practice Sign Language and also people who don't know can learn through this

Hand Gesture Recognition System using OpenCV and Python

An attention based approach to convert Indian Sign Language to Text using simulated hand gesture data

a vertical scroller game where players steer their spaceship with hand movements, dodging asteroids and aiming for high scores.

AG-MAE: Anatomically Guided Spatio-Temporal Masked Auto-Encoder for Online Hand Gesture Recognition

The project leverages MediaPipe for hand tracking to create a virtual mouse interface, enabling precise cursor control and clicking through intuitive hand gestures. It translates real-time hand movements into mouse actions using a webcam, offering a hands-free interaction experience.

You Can Wash Hands Better: Accurate Daily Handwashing Assessment with Smartwatches

Real-time body, face and hand gesture detection from live webcam feed - A Computer Vision and Image Processing project.

This Modulator lets you control your device's audio with a wave of your hand.

Detects Gestures using Keras Model

This Python application enables control of the mouse cursor through hand gestures captured via webcam. It leverages Mediapipe for hand tracking and OpenCV for video processing, allowing users to perform actions like moving the cursor, left-clicking, right-clicking, dragging, and scrolling using intuitive gestures.

A hand gesture control with facial authentication for the DJI Tello drone. The system uses computer vision (openCV) and machine learning techniques to ensure secure and intuitive drone control. Gestures work only if an authorized face is detected; otherwise, the drone lands after 20 seconds of not detecting any face.

This project implements a hand gesture recognition system using deep learning techniques with TensorFlow and Keras. It involves preprocessing a dataset from Kaggle, building and training a convolutional neural network (CNN) model.

This project is a virtual painting application that permits users to draw and paint directly onto the live camera stream. It has been developed using Python, OpenCV, and MediaPipe.

Hand Gesture Media Player Controler with OpenCV

Hand gesture recognition system with an mobile app to play a game of Rock-Paper-Scissors

Developing a pipeline for Hand Gesture Recognition