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.

generate arbitrary handwritten letter/digits based on the inputs

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

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

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

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

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

A deep learning model deployed as a web app to classify handwritten digits and letters using the EMNIST dataset

Projekti rađeni u programskom jeziku Python. Svi projekti su vezani uz tematiku podatkovne analitike i podatkovne znanosti.

2020/2021 sem 2 - Neural Network Individual Assignment Project - EMNIST prediction - Predict and evaluate the output of model trained using multiple MLP model created by using the EMNIST datasets.

Simple parser of emnist letters

TextToHandwriting tool

User handwriting recognition app using a CNN trained on the EMNIST ByClass dataset

Machine learning models.