Pinned Repositories
fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
flow-functions
Flow function examples for flows.network
ICDAR2019_cTDaR
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.
kleister-charity
kleister-nda
kosmos2-5_fairseq
LeetCode
NLP-practice-program
力求囊括主流NLP模型练手项目，不断更新中
Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
VT-SSum
Dod-o's Repositories
Dod-o/Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
Dod-o/NLP-practice-program
力求囊括主流NLP模型练手项目，不断更新中
Dod-o/LeetCode
Dod-o/VT-SSum
Dod-o/fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Dod-o/flow-functions
Flow function examples for flows.network
Dod-o/ICDAR2019_cTDaR
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.
Dod-o/kleister-charity
Dod-o/kleister-nda
Dod-o/kosmos2-5_fairseq
Dod-o/unilm
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities