Titlebook: Proceedings of the Future Technologies Conference (FTC) 2024, Volume 3; Kohei Arai Conference proceedings 2024 The Editor(s) (if applicabl

字形刻痕

Salma Alghamdi,Lama Al Khuzayem,Ohoud Al-Zamzamisis with varied levels of noise confirms the promising results of character recognition accuracy of the proposed OCR model which out-performs the state-of-the-art OCR systems for Indian scripts. The proposed model achieves 76.70% with test documents consists of 50% noise and 99.98% with test documen

NIL

Razan Al-Hamed,Rawan Al-Hamed,Aya Karam,Fatima Al-Qattan,Fatmah Al-Nnaimy,Soraia Oueidand reach a performance similar to the base approach on flat entities. Even though all 3 approaches perform well in terms of F1-scores, joint labelling is most suitable for hierarchically structured data. Finally, our experiments reveal the superiority of the IO tagging format on such data.

CAB

Blazon

Cursory

Vasanth Iyer,Igor Ternovskiycy improves significantly, inference time is halved compared to HTML-based models, and the predicted table structures are always syntactically correct. This in turn eliminates most post-processing needs. Popular table structure data-sets will be published in OTSL format to the community.

Mortar

anaphylaxis

neutralize

JOG

Cencheng Shendictive at word image level compared to classical static embedding methods. Furthermore, our recognition-free approach with pre-trained semantic information outperforms recognition-free as well as recognition-based approaches from the literature on several Named Entity Recognition benchmark datasets

Glutinous