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

CNN and Contrastive Autoencoder (CAE) on EMNIST using Tensorflow

Handwritten text recognition using CNN with EMNIST dataset

Handwritten character recognition on EMNIST ByClass using Convolutional Neural Networks with PyTorch.

Python scripts for decoding the EMNIST dataset

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

Handwriting Digit & Character Recognition (Flask + TensorFlow)

Pytorch implementation of Generative Adversarial Networks (GAN) for MNIST and EMNIST datasets

Bachelor Degree Project in Information Technology

A CNN-based OCR system that extracts both typed and handwritten text from images. Using a multi-layered convolutional neural network trained on the EMNIST dataset, it processes images through hierarchical contour detection to identify and recognize alphanumeric characters. Ideal for document digitization and text extraction applications.

Handwriting to Digital Text using CNNs - 2019 - Yildiz Technical University, Istanbul

7-layer CNN

Saving MNIST dataset in separate folders as jpg

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

Custom dataset for training and testing AI OCR models.

Deep Learning journey with PyTorch: CNN implementations for EMNIST digit recognition & CIFAR-10 classification + comprehensive learning exercises

Generative Adversarial Networks for generating Extended-MNIST samples

A Convolutional Neural Network for EMNIST dataset