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.
-
Updated
Dec 9, 2024 - Python
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.
Official PyTorch Implementation of "WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models" - ICDAR 2023
Easter2.0: IMPROVING CONVOLUTIONAL MODELS FOR HANDWRITTEN TEXT RECOGNITION
Improved Text recognition algorithms on different text domains like scene text, handwritten, document, Chinese/English, even ancient books
Basic HTR concepts/modules to boost performance
handwritten word recognition with IAM dataset using CNN-Bi-LSTM and Bi-GRU implementation.
English Handwriting Recognition with CRNN and CTC Loss
Pytorch implementation of HTR on IAM dataset (word or line level + CTC loss)
Train a Text Recognition CRNN model with Tensorflow2 & Keras & IAM Dataset. Convolutional Recurrent Neural Network. CTC.
This project shows how to build a simple handwriting recognizer in Keras with the IAM dataset.
Deformation-invariant line-level Handwritten Text Recognition (HTR) using a convolutional-only architecture.
Benchmark of different network architectures for handwritten text recognition.
Implementation of Handwritten Text Recognition Systems using TensorFlow
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).
Handwriting Recognition Project
Models for handwriting generation for academic purposes (My Bachelor thesis)
Add a description, image, and links to the iam-dataset topic page so that developers can more easily learn about it.
To associate your repository with the iam-dataset topic, visit your repo's landing page and select "manage topics."