Handwriting Recognition Project

Models for handwriting generation for academic purposes (My Bachelor thesis)

An ongoing & curated collection of awesome software best practices and remediation techniques, libraries and frameworks, E-books and videos, Technical guidelines and important resources about Identiy & Access Management (IAM).

Implementation of Handwritten Text Recognition Systems using TensorFlow

Benchmark of different network architectures for handwritten text recognition.

Deformation-invariant line-level Handwritten Text Recognition (HTR) using a convolutional-only architecture.

This project shows how to build a simple handwriting recognizer in Keras with the IAM dataset.

handwritten word recognition with IAM dataset using CNN-Bi-LSTM and Bi-GRU implementation.

Train a Text Recognition CRNN model with Tensorflow2 & Keras & IAM Dataset. Convolutional Recurrent Neural Network. CTC.

Pytorch implementation of HTR on IAM dataset (word or line level + CTC loss)

Basic HTR concepts/modules to boost performance

English Handwriting Recognition with CRNN and CTC Loss

Official PyTorch Implementation of "WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models" - ICDAR 2023

Improved Text recognition algorithms on different text domains like scene text, handwritten, document, Chinese/English, even ancient books

Easter2.0: IMPROVING CONVOLUTIONAL MODELS FOR HANDWRITTEN TEXT RECOGNITION

Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.