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The ICDAR 2019 cTDaR is to evaluate the performance of methods for table detection (TRACK A) and table recognition (TRACK B). For the first track, document images containing one or several tables are provided. For TRACK B two subtracks exist: the first subtrack (B.1) provides the table region. Thus, only the table structure recognition must be performed. The second subtrack (B.2) provides no a-priori information. This means, the table region and table structure detection has to be done.

Last commit Jan 14, 2022

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Last commit Jun 19, 2020

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MineContext is your proactive context-aware AI partner(Context-Engineering+ChatGPT Pulse)

Last commit May 29, 2026

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力求囊括主流NLP模型练手项目,不断更新中

Last commit Jun 11, 2020

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手写实现李航《统计学习方法》书中全部算法

Last commit Nov 25, 2023

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Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Last commit Dec 26, 2021

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Flow function examples for flows.network

Last commit Oct 28, 2022

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Last commit Nov 19, 2020

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Last commit Apr 25, 2024

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Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

Last commit Nov 16, 2022

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MCP for xiaohongshu.com

Last commit May 29, 2026

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