Convert typed text to realistic handwriting!

Alphabet recognition using EMNIST dataset for humans ⚓

✍️ Convolutional Recurrent Neural Network in Pytorch | Text Recognition

Handwriting recoginition program made using CNN in Python.

Teaching a neural network how to write letters and digits with reinforcement learning.

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

generate arbitrary handwritten letter/digits based on the inputs

Digits Recognizer using correlation and similarity methods in MNIST Letters dataset.

EMNIST Character Recognizer : Draw a character, and the app instantly predicts it using a PyTorch model trained on EMNIST—all in a simple Tkinter interface.

Exploring advanced autoencoder architectures for efficient data compression on EMNIST dataset, focusing on high-fidelity image reconstruction with minimal information loss. This project tests various encoder-decoder configurations to optimize performance metrics like MSE, SSIM, and PSNR, aiming to achieve near-lossless data compression.

Project 3 for Artificial Neural Networks

A simple NN word recognizer based on the EMNIST dataset

Simple parser of emnist letters

This is the code for my IB Extended Essay in Computer Science

Handwritten Character Recognition is a web application built with Flask that enables users to draw handwritten letters and receive real-time predictions using a deep learning model.

Natural Language Processing Model that can recognise handwritten letters and convert them to typed text.

A modular neural network implemented from scratch in Python. Includes customizable architecture, training with backpropagation, evaluation metrics, and visualizations using the EMNIST dataset.

detecting hand written digits and letters from images (+camera) (EMNIST) (tensorflow)

Keras를 활용한 손글씨 교정 사이트 (‘20 제 14회 공개 SW 개발자 대회)

Library to read the EMNIST and MNIST data sets