US 12,444,163 B2
Apparatus and methods for converting lineless tables into lined tables using generative adversarial networks
Mehrdad Jabbarzadeh Gangeh, Mountain View, CA (US); and Hamid Reza Motahari Nezad, Los Altos, CA (US)
Assigned to EYGS LLP, London (GB)
Filed by EYGS LLP, London (GB)
Filed on Jan. 23, 2024, as Appl. No. 18/419,946.
Application 18/419,946 is a continuation of application No. 16/546,938, filed on Aug. 21, 2019, granted, now 11,915,465.
Prior Publication US 2024/0161449 A1, May 16, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 30/412 (2022.01); G06F 16/25 (2019.01); G06N 3/045 (2023.01); G06N 3/088 (2023.01); G06V 10/44 (2022.01); G06V 10/82 (2022.01); G06V 30/19 (2022.01); G06V 30/414 (2022.01)
CPC G06V 10/454 (2022.01) [G06F 16/258 (2019.01); G06N 3/045 (2023.01); G06N 3/088 (2013.01); G06V 10/82 (2022.01); G06V 30/19173 (2022.01); G06V 30/412 (2022.01); G06V 30/414 (2022.01)] 19 Claims
OG exemplary drawing
 
1. A non-transitory, processor-readable medium comprising code that when executed cause a processor to:
remove, using a mask, at least some lines from a first set of tables to generate a second set of tables;
train a conditional generative adversarial network (cGAN), using the first set of tables and the second set of tables, to produce a trained cGAN, the cGAN including a generative algorithm and a discriminative algorithm, the discriminative algorithm configured to authenticate table pairs from the first set of tables and the second set of tables based on a predicted table produced by the generative algorithm, each of the generative algorithm and the discriminative algorithm including at least one convolutional neural network layer;
identify, using the trained cGAN, a plurality of lines for overlaying onto a lineless table; and
overlay the plurality of lines onto the lineless table to produce a lined table.