Handwritten Digit Recognition using Machine Learning and Deep Learning

:pencil2: :cloud: The easy way to integrate mathematical expressions handwriting recognition in your web app.

(Pattern Recognition) Pytorch implementation of “HTR-VT: Handwritten Text Recognition with Vision Transformer”

Using OpenCV in python to recognize digits in a scanned page of handwritten digits.

Handwritten digit recognition with MNIST & Keras

Convert hand written mathematical expressions and formula to Latext using Machine Learning

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

Extract and solve sudoku from an image using Computer Vision and Deep Learning

Hand Written Digit Recognition

Handwritten Digit Recognition Using Convolutional Neural Network by Python

🎰Handwritten digit recognition application implemented by TensorFlow2 + Keras and Flask.

Real time MNIST digit recognition with OpenCV and Support Vector Machine (SVM) algorithm.

Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

The purpose of this project is to take handwritten digits as input, process the digits, train the neural network algorithm with the processed data, to recognize the pattern and successfully identify the test digits. The popular MNIST dataset is used for the training and testing purposes. The IDE used is MATLAB

This project demonstrates Handwritten digit recognition using Deep Learning

Recognize handwritten multi-digit numbers using a CRNN model trained with synthetic data.

A computer vision project, based on cimg library and svm training, to classify handwriting number.

MNIST·扩展数据集·手写识别计算器·多目标检测·可解释性分析·可视化·handwriting recognition calculator·multi-target detection·explainability·extended dataset

Iranian cars number plate detection and recognition

A handwritten digit recognition painter implementation on Basys 3 Artix-7 FPGA using Verilog.

An open source Verilog Based LeNet-1 Parallel CNNs Accelerator for FPGAs in Vivado 2017

This project offers an efficient method for identifying and recognizing handwritten text from images. Using a Convolutional Recurrent Neural Network (CRNN) for Optical Character Recognition (OCR), it effectively extracts text from images, aiding in the digitization of handwritten documents and automated text extraction.

Recognize Handwritten Digits - A Simple Web App

A modified extractor for the CROHME handwritten math symbols dataset.

Handwritten Formula Recognition | 手写公式识别

Pytorch implementation of a Variational Autoencoder (VAE) that learns from the MNIST dataset and generates images of altered handwritten digits.

A neural network built in Verilog for the DE1-SoC FPGA board for handwritten digit recognition.

✏️ An AI-driven web app for handwritten digit recognition using the MNIST dataset. It leverages TensorFlow for deep learning model training and Gradio to create an intuitive, interactive UI. Users can draw digits and receive instant predictions, showcasing practical AI deployment and real-time inference capabilities.

automatic analysis of scanned documents(only extracting handwritten digits)

Handwriting Recognition using ML.NET