Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi

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GraphMLLM: A Graph-Based Multi-level Layout Language-Independent Model for?Document Understandingiversity of document languages and structures, there is still room to better model various document layouts while efficiently utilizing the pre-trained language models. To this goal, this paper proposes a Graph-based Multi-level Layout Language-independent Model (GraphMLLM) which uses dual-stream st

異教徒

飛鏢

臭了生氣

卜聞

https://doi.org/10.1007/978-3-662-10287-9 Our method processes video clips captured with smartphones under common lighting conditions, and is evaluated on two public datasets: MIDV-HOLO and MIDV-2020. Thanks to a weakly-supervised training, we optimize a feature extraction and decision pipeline which achieves a new leading performance on M

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旁觀者

vitreous-humor

茁壯成長

https://doi.org/10.1007/978-1-4615-3296-5ound that current slide datasets contain inconsistencies, mislabels, and incomplete annotations. Using them as a basis for developing deep learning-based slide analysis models could lead to models that are not robust and suboptimal. Addressing these challenges, we introduce SlideCraft, a tool for cr