Alphabet recognition using EMNIST dataset for humans ⚓

This algorithm is integrated with anvil website which identifies the alphabet present in the given input image.

Neural Network model for English alphabet recognition. Deep learning engine - PyTorch

Deep Learning algorithm in pytorch to detect Hindi Alphabets given in form of images

This project recognizes alphabet gestures real time using the camera feed. The project uses two ML models for prediction, one is using a CNN and the other uses normal neural networks.

This is a simple app to predict the alphabet that is written on the screen using an object of interest.

simple alphabet reader

Handwritten Alphabet & Digit Recognition Web Application

Simple American Sign Language detector using KNN.

A web-based tool that recognizes handwritten digits and alphabets using a Convolutional Neural Network (CNN) trained on the MNIST and EMNIST datasets. The system is built with Flask and TensorFlow, offering an intuitive interface for character recognition.

ElderWand-JetsonNano is an AI-powered gesture recognition system for NVIDIA Jetson Nano. It uses CUDA-accelerated OpenCV to detect wand movements in real-time, triggering GPIO actions like controlling lights or unlocking a solenoid lock. Designed for the Jetson AI Ambassador Program.

Alphabet Recognition Model using Python.

This repository contains a project focused on handwritten digit classification using a Convolutional Neural Network (CNN). The goal was to classify digits (0-9) from the widely-used MNIST dataset.