Invention Publication
- Patent Title: METHODS AND SYSTEMS FOR USING TRAINED GENERATIVE ADVERSARIAL NETWORKS TO IMPUTE 3D DATA FOR CONSTRUCTION AND URBAN PLANNING
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Application No.: US18618673Application Date: 2024-03-27
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Publication No.: US20240242316A1Publication Date: 2024-07-18
- Inventor: Ryan Knuffman
- Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
- Applicant Address: US IL Bloomington
- Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
- Current Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
- Current Assignee Address: US IL Bloomington
- Main IPC: G06T5/77
- IPC: G06T5/77 ; G06N3/045 ; G06N3/088 ; G06T7/579

Abstract:
A computer-implemented method for using a trained generative adversarial network to improve construction and urban planning includes receiving a semantically-segmented point cloud corresponding to a construction site; determining a volumetric soil measurement; and generating a cost estimate. A computing system for using a trained generative adversarial network to improve vehicle orientation and navigation includes one or more processors, and one or more memories having stored thereon computer-executable instructions that, when executed, cause the computing system to: receive a semantically-segmented point cloud corresponding to a construction site; determine a volumetric soil measurement; and generate a cost estimate. A non-transitory computer-readable medium includes computer-executable instructions that, when executed, cause a computer to: receive a semantically-segmented point cloud corresponding to a construction site; determine a volumetric soil measurement; and generate a cost estimate.
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