✍️ Convolutional Recurrent Neural Network in Pytorch | Text Recognition
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Updated
May 1, 2019 - Jupyter Notebook
✍️ Convolutional Recurrent Neural Network in Pytorch | Text Recognition
Teaching a neural network how to write letters and digits with reinforcement learning.
generate arbitrary handwritten letter/digits based on the inputs
Project 3 for Artificial Neural Networks
Handwriting recoginition program made using CNN in Python.
Keras를 활용한 손글씨 교정 사이트 (‘20 제 14회 공개 SW 개발자 대회)
Projekti rađeni u programskom jeziku Python. Svi projekti su vezani uz tematiku podatkovne analitike i podatkovne znanosti.
This is a simple app to predict the alphabet that is written on the screen using an object of interest.
Alphabet recognition using EMNIST dataset for humans ⚓
Dask-parallelized project, contrasting GaussianNB and LightGBM models for EMNIST handwritten character classification.
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.
TextToHandwriting tool
Library to read the EMNIST and MNIST data sets
This project aims to implement AI-driven letter recognition using neural network libraries and the EMNIST dataset. By employing deep learning and data preprocessing, we seek to build a versatile system for accurately identifying letters in both handwritten and printed text, with applications in OCR and document digitization.
User handwriting recognition app using a CNN trained on the EMNIST ByClass dataset
A simple NN word recognizer based on the EMNIST dataset
Evaluating the accuracy with different CNN kernel sizes for the EMNIST Balanced dataset
This is the code for my IB Extended Essay in Computer Science
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