US 11,676,411 B2
Systems and methods for neuronal visual-linguistic data retrieval from an imaged document
Amos Simantov, Hod Hasharon (IL); Roy Shilkrot, Kibbutz Negba (IL); Nimrod Morag, Hod Hasharon (IL); and Rinon Gal, Tel-Aviv (IL)
Filed by WAY2VAT LTD., Tel-Aviv (IL)
Filed on Dec. 28, 2020, as Appl. No. 17/134,597.
Application 17/134,597 is a continuation of application No. 16/500,102, granted, now 10,936,863, previously published as PCT/IB2018/058891, filed on Nov. 13, 2018.
Claims priority of provisional application 62/642,686, filed on Mar. 14, 2018.
Claims priority of provisional application 62/585,116, filed on Nov. 13, 2017.
Prior Publication US 2021/0117665 A1, Apr. 22, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. G06K 9/62 (2022.01); G06V 30/412 (2022.01); G06N 20/00 (2019.01); G06N 3/08 (2023.01); G06Q 30/04 (2012.01)
CPC G06V 30/412 (2022.01) [G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06Q 30/04 (2013.01)] 32 Claims
OG exemplary drawing
 
19. An expense management platform operable to perform automatic data retrieval from an imaged invoice document, said expense management platform comprising:
an automatic invoice analyzer (AIA) operable to perform automated analysis of the imaged invoice document;
a machine learning engine comprising a knowledge repository, said machine learning engine operable to update the knowledge repository with data pertaining to said invoice imaged document; and
a neuronal visual-linguistic mechanism trained to perform visual-linguistic semantic analysis;
wherein said neuronal visual-linguistic mechanism comprises a geometrically trained neuronal network, such that said expense management platform is operable to produce one or more analysis results using said neuronal visual-linguistic mechanism to determine geometric-semantic information.