A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.
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Updated
Oct 26, 2018 - Python
A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.
Software to recognize handwriting
Alphabet recognition using EMNIST dataset for humans ⚓
Classify EMNIST Digits using Convolutional Neural Networks
emnist pytorch LeNet CNN gpu
CNN and Contrastive Autoencoder (CAE) on EMNIST using Tensorflow
A comparison of RCN/CNN/SVM/KNN on EMNIST-letters dataset
Use Tensorflow Keras to train a image classification model on both MNIST and EMNIST letters.
Get 99.13% test accuracy MNIST with only 300 lines of code CNN by JAVA
Pytorch implementation of Generative Adversarial Networks (GAN) for MNIST and EMNIST datasets
DACON - 글자에 숨겨진 숫자 이미지 예측 (MNIST 변형)
EMNIST English letters OCR machine learning model using Random Forests (RF) and Decision Trees (DT) algorrithms.
In this project, text is extracted from an image and is converted into text format. This project only works where text is in Capital Letters.
Python GUI for handwriting recognition CNN with 80% accuracy trained on the EMNIST dataset with detailed documentation included.
Neural network to classify the EMNIST dataset
Handwritten Character Recognition. EMNIST dataset on Kaggle. Tensorflow2 - Keras - CNN - 0.85 evaluation.
Handwritten text recognition using CNN with EMNIST dataset
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