This repository lets you train neural networks models for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.
Appears on
Quick read
Latest capture 2026-11-09 09:38
Compare the starting count and capture dates, not just the percentage. How to read GitHub star growth. Missing history is not zero growth.
Archive status reflects the last catalog sync, not a maintenance assessment. Check recent releases, issue responses, and fit for your project with the repository shortlisting checklist.
0 paths
Agent instructions and tool configuration found in this repository.
No config files detected.
1 observed capture since 2026-11-09. Observed captures are shown by default.
Stars from first capture 0
Observed captures only
All tracked data
Observed snapshots
Observed snapshots
Nearest indexed repositories by embedding similarity.
No description.
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.
Handwritten Text Recognition (HTR) system implemented with TensorFlow.
Handwriting Recognition System based on a deep Convolutional Recurrent Neural Network architecture
Pytorch implementation for "Decoupled attention network for text recognition".
Handwritten Text Recognition
