ICDAR 2019 Tutorial on Deep Learning for Document Analysis

This repository contains a number of worksheets and presentations that show how to use the collection of PyTorch-based OCRopus components.

The presentations are numbered, so it's recommended that you read the in order.

There are companion worksheets with full implementations of many of the models; these will be published separately.

Name		Name	Last commit message	Last commit date
Latest commit History 27 Commits
OLD		OLD
figs		figs
010-overview.ipynb		010-overview.ipynb
100-foundations.ipynb		100-foundations.ipynb
110-modern-dl.ipynb		110-modern-dl.ipynb
120-convnet-ocr.ipynb		120-convnet-ocr.ipynb
130-recurrent-networks.ipynb		130-recurrent-networks.ipynb
150-layout.ipynb		150-layout.ipynb
160-neural-transducers.ipynb		160-neural-transducers.ipynb
200-augmentation.ipynb		200-augmentation.ipynb
210-pytorch.ipynb		210-pytorch.ipynb
220-dataloader.ipynb		220-dataloader.ipynb
230-digits-intro.ipynb		230-digits-intro.ipynb
300-localization.ipynb		300-localization.ipynb
LICENSE		LICENSE
README.md		README.md

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