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  ---
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  pipeline_tag: image-to-text
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- tags:
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- - 'arxiv:2504.03349'
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  # Meta-DAN
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  This repository contains official trained model weights from the paper:
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  Denis Coquenet, "Meta-DAN: towards an efficient prediction strategy for page-level handwritten text recognition", Pattern Recognition, 2026.
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- The paper is available [here](https://doi.org/10.1016/j.patcog.2026.113373).
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  The source code is available [here](https://github.com/FactoDeepLearning/META-DAN).
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  Weights are given for the following models: DAN (TPAMI 2023), Faster DAN (ICDAR 2023), MT-DAN (PR 2026), W-DAN (PR 2026) and Meta-DAN (PR 2026).
 
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  pipeline_tag: image-to-text
 
 
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  # Meta-DAN
 
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  This repository contains official trained model weights from the paper:
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  Denis Coquenet, "Meta-DAN: towards an efficient prediction strategy for page-level handwritten text recognition", Pattern Recognition, 2026.
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+ The paper is published in [Pattern Recognition](https://doi.org/10.1016/j.patcog.2026.113373). Also available on [Arxiv](https://arxiv.org/abs/2504.03349).
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  The source code is available [here](https://github.com/FactoDeepLearning/META-DAN).
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  Weights are given for the following models: DAN (TPAMI 2023), Faster DAN (ICDAR 2023), MT-DAN (PR 2026), W-DAN (PR 2026) and Meta-DAN (PR 2026).