US 12,430,815 B2
Predicting object deformation using a generative adversarial network model
Sarbajit K. Rakshit, Kolkata (IN); Sathya Santhar, Ramapuram (IN); and Sridevi Kannan, Chennai (IN)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Dec. 19, 2023, as Appl. No. 18/544,826.
Prior Publication US 2025/0200824 A1, Jun. 19, 2025
Int. Cl. G06T 11/00 (2006.01); G06N 3/0475 (2023.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G06V 20/52 (2022.01)
CPC G06T 11/00 (2013.01) [G06N 3/0475 (2023.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G06V 20/52 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
identifying, based on an analysis of image data, a plurality of objects that are in a first stack formation;
determining a load distribution of each object of the plurality of objects in relation to a subset of objects of the plurality of objects in the first stack formation;
generating, using a generative adversarial network (GAN) algorithm and based on the load distribution for each object, a visualization depicting deformation of each object of the plurality of object in relation to the subset of objects of the plurality of objects in the first stack formation; and
displaying the visualization depicting the deformation of each object of the plurality of objects to a user.