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Delivering Document Conversion as a Cloud Service with High Throughput and Responsiveness. (arXiv:2206.00785v1 [cs.DL])
June 3, 2022, 1:12 a.m. | Christoph Auer (1), Michele Dolfi (1), André Carvalho (2), Cesar Berrospi Ramis (1), Peter W. J. Staar (1) ((1) IBM Research, (2) SoftINSA Lda.)
cs.CV updates on arXiv.org arxiv.org
Document understanding is a key business process in the data-driven economy
since documents are central to knowledge discovery and business insights.
Converting documents into a machine-processable format is a particular
challenge here due to their huge variability in formats and complex structure.
Accordingly, many algorithms and machine-learning methods emerged to solve
particular tasks such as Optical Character Recognition (OCR), layout analysis,
table-structure recovery, figure understanding, etc. We observe the adoption of
such methods in document understanding solutions offered by all …
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