There are 2 repositories under emnist topic.
A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.
Alphabet recognition using EMNIST dataset for humans ⚓
Software to recognize handwriting
emnist pytorch LeNet CNN gpu
Get 99.13% test accuracy MNIST with only 300 lines of code CNN by JAVA
A comparison of RCN/CNN/SVM/KNN on EMNIST-letters dataset
CNN and Contrastive Autoencoder (CAE) on EMNIST using Tensorflow
Handwritten Character Recognition. EMNIST dataset on Kaggle. Tensorflow2 - Keras - CNN - 0.85 evaluation.
Use Tensorflow Keras to train a image classification model on both MNIST and EMNIST letters.
A small computer vision project in the making. Partners: Minh Quan Huynh and Duc Minh Hoang.
Handwritten text recognition using CNN with EMNIST dataset
Teaching a neural network how to write letters and digits with reinforcement learning.
Python scripts for decoding the EMNIST dataset
A neural network project written in Rust.
A web app for recognizing handwritten characters and digits.
Handwritten character recognition on EMNIST ByClass using Convolutional Neural Networks with PyTorch.
emnist example (0-9 and a-z and A-Z - 28x28) [kotlin + gradle support]
EMNIST English letters OCR machine learning model using Random Forests (RF) and Decision Trees (DT) algorrithms.
Convolutional Neural Network for classifying drawn alphanumeric characters using EMNIST/MNIST datasets, with a Vue.js Canvas UI, as a PWA.
Bachelor Degree Project in Information Technology
Pytorch implementation of Generative Adversarial Networks (GAN) for MNIST and EMNIST datasets
User handwriting recognition app using a CNN trained on the EMNIST ByClass dataset
This iOS app allows users to draw characters and numbers on a drawing view, and a machine learning model will recognize the input, displaying the results just below the drawing area. The underlying model was created as part of the Intro to Machine Learning course and converted from PyTorch to CoreML using coremltools
A brand-new dataset created by utilizing the characters provided by the EMNIST dataset and putting them into sequences
First dive into designing convolutional neural networks for image recognition
A Convolutional Neural Network for EMNIST dataset
Translator from KMNIST encoded pages to readable EMNIST, based on unsupervised learning algorithms.
Codes regarding the paper: Handwritten Image Detection using DCGAN with SIFT and ORB Optical Features
Python GUI for handwriting recognition CNN with 80% accuracy trained on the EMNIST dataset with detailed documentation included.