The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 24, 2024

Filed:

Dec. 21, 2020
Applicant:

Bentley Systems, Incorporated, Exton, PA (US);

Inventors:

Marc-André Gardner, Quebec City, CA;

Karl-Alexandre Jahjah, Quebec City, CA;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/2415 (2023.01); G06F 40/242 (2020.01); G06N 5/04 (2023.01); G06V 10/22 (2022.01); G06V 30/10 (2022.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/2415 (2023.01); G06F 40/242 (2020.01); G06N 5/04 (2013.01); G06V 10/22 (2022.01); G06V 30/10 (2022.01);
Abstract

In example embodiments, techniques are provided for using machine learning to extract machine-readable labels for text boxes and symbols in P&IDs in image-only formats. A P&ID data extraction application uses an optical character recognition (OCR) algorithm to predict labels for text boxes in a P&ID. The P&ID data extraction application uses a first machine learning algorithm to detect symbols in the P&ID and return a predicted bounding box and predicted class of equipment for each symbol. One or more of the predicted bounding boxes may be decimate by non-maximum suppression to avoid overlapping detections. The P&ID data extraction application uses a second machine learning algorithm to infer properties for each detected symbol having a remaining predicted bounding box. The P&ID data extraction application stores the predicted bounding box and a label including the predicted class of equipment and inferred properties in a machine-readable format.


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