Method and Apparatus for Determining Physical State of Object via Neural Network
Summary
USPTO published patent application US20260093961A1 for a computer-implemented method using neural networks to determine physical states of objects. The method divides object shapes into sub-shapes, computes local solutions via a neural network model, and derives global solutions representing the object's physical state. Invented by Jianing Huang, Youjia Wu, Kaixuan Zhang, and Ze Cheng. This is an informational publication with no regulatory obligations.
What changed
USPTO published patent application US20260093961A1 on April 2, 2026, covering a computer-implemented method for determining the physical state of an object through neural networks. The method involves dividing an object's shape into sub-shapes, obtaining local solutions for each sub-shape via a neural network model based on global boundary conditions, and combining these into a global solution representing the object's physical state. The application (No. 19342526) was filed on September 27, 2025.
This patent application publication is informational only and creates no compliance obligations for regulated entities. Technology companies developing AI systems for physical state analysis should review the published claims to assess potential patent landscape implications. No action is required unless the company is involved in similar technology development where this publication may constitute prior art.
Archived snapshot
Apr 2, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
METHOD AND APPARATUS FOR DETERMINING PHYSICAL STATE OF AN OBJECT
Application US20260093961A1 Kind: A1 Apr 02, 2026
Inventors
Jianing Huang, Youjia Wu, Kaixuan Zhang, Ze Cheng
Abstract
A computer-implemented method for determining the physical state of an object having a shape includes (i) dividing the shape of the object into a plurality of sub-shapes, (ii) obtaining a local solution for each of the plurality of sub-shapes through a neural network model based on a global boundary condition for the shape and the plurality of sub-shapes, wherein the local solution for each sub-shape represents the local physical state of the object having the sub-shape, and (ii) obtaining a global solution for the shape based on the local solution for each sub-shape in the plurality of sub-shapes, wherein the global solution for the shape represents the physical state of the object.
CPC Classifications
G06N 3/0475 G06N 3/08
Filing Date
2025-09-27
Application No.
19342526
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