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English(EN) ExpertHTR: Unified Handwritten Text Recognition with Multi-Task Learning and Sparse Mixture-of-Experts

ExpertHTR框架通过多任务学习统一手写文本识别

研究人员推出ExpertHTR,一个旨在统一跨不同数据集的手写文本识别(HTR)的新框架。该系统采用多任务学习和稀疏专家混合(Mixture-of-Experts)架构,以有效处理语言、字体和标注格式的差异。实验表明,ExpertHTR在多个基准测试中显著优于通用的OCR和视觉语言系统,在IAM段落级数据集上取得了最先进的成果,尽管在某些具有挑战性的数据集上,专用HTR系统仍占有优势。 AI

影响 这项研究有望提高处理各种手写文档的准确性和效率,造福档案和数据录入应用。

排序理由 该条目描述了一篇详细介绍新模型架构及其实验结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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ExpertHTR框架通过多任务学习统一手写文本识别

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该条目描述了一篇详细介绍新模型架构及其实验结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Dang Hoai Nam, Nguyen Duy Hieu, Quang Huu Hieu, Vo Nguyen Le Duy ·

    ExpertHTR:多任务学习与稀疏专家混合的统一手写文本识别

    arXiv:2609.12705v1 Announce Type: cross Abstract: Handwritten text recognition resources are often small and distributed across collections that differ in language, script, document structure, and annotation format, making joint page-level training difficult. We propose ExpertHTR…