Handwritten digits, a bit like the MNIST dataset.

A simple, easy to use MNIST loader written in Python 3

MNIST Database of Handwritten Digits for MATLAB

Handwritten Number Recognition using CNN and Character Segmentation

Easy to use CMATERdb datasets converted in NumPy format

Trains a Neural Network to read handwritten digits (OCR). Uses synaptic for Node.js, socket.io and MongoDB

Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI

Python implementation of a Yatzy score sheet detection using OpenCV, TensorFlow, MNIST

Collection of Machine Learning Algorithms

Handwritten digit classification web app using Streamlit

MNIST Database of Handwritten Digits

Digit recognition using SVM

Generate handwritten digits using Gans

Generation of Human-Like handwritten digits using different GAN Architectures. The models were developed using Low-Level Tensorflow.

a OCR for digits using MNIST dataset

Handwritten Digits and Alphabets Recognition using Convolutional Neural Networks

MNIST handwritten digit classification using PyTorch

A collection of 107,730 28x28 PNG files of digits from 0-9, with a dataset generator.

This project offers a simple and intuitive interface for users to input text and generate images that showcase the text in a handwritten style. The generator supports several stylistic modifications including bold, underline, and color alterations, allowing users to create personalized and visually appealing images from their text.

Using Multi Layer Perceptron to build the model. Classifies the handwritten digits of the MNIST database with around 98% accuracy.