Information Extraction from Invoices

Author:

Hamdi AhmedORCID,Carel ElodieORCID,Joseph AurélieORCID,Coustaty MickaelORCID,Doucet AntoineORCID

Publisher

Springer International Publishing

Reference26 articles.

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2. Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional LSTM-CNNs. arXiv preprint arXiv:1511.08308 (2015)

3. Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12, 2493–2537 (2011)

4. Conneau, A., Lample, G.: Cross-lingual language model pretraining. In: Wallach, H., Larochelle, H., Beygelzimer, A., d’ Alché-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32, pp. 7059–7069. Curran Associates, Inc. (2019). http://papers.nips.cc/paper/8928-cross-lingual-language-model-pretraining.pdf

5. Dengel, A.R., Klein, B.: smartFIX: a requirements-driven system for document analysis and understanding. In: Lopresti, D., Hu, J., Kashi, R. (eds.) International Workshop on Document Analysis Systems, DAS 2002. LNCS, vol. 2423, pp. 433–444. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45869-7_47

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1. A Two-stage Approach for Tables Extraction in Invoices;2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI);2023-11-06

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5. Query-driven Generative Network for Document Information Extraction in the Wild;Proceedings of the 30th ACM International Conference on Multimedia;2022-10-10

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