US 12,299,719 B2
Processing system having a machine learning engine for providing a surface dimension output
David M. Zahn, Lake Villa, IL (US); Andrew Daniels, Columbus, OH (US); Pinal Patel, Libertyville, IL (US); David L. Gilkison, Libertyville, IL (US); and Steven Genc, Hainesville, IL (US)
Assigned to Allstate Insurance Company, Northbrook, IL (US)
Filed by Allstate Insurance Company, Northbrook, IL (US)
Filed on Aug. 23, 2022, as Appl. No. 17/893,995.
Application 17/893,995 is a continuation of application No. 16/131,320, filed on Sep. 14, 2018, granted, now 11,436,648.
Application 16/131,320 is a continuation in part of application No. 15/971,294, filed on May 4, 2018, granted, now 11,257,132, issued on Feb. 2, 2022.
Prior Publication US 2022/0405816 A1, Dec. 22, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/0283 (2023.01); G06N 20/00 (2019.01); G06Q 40/08 (2012.01); G06T 7/00 (2017.01); G06T 7/13 (2017.01); G06T 7/62 (2017.01)
CPC G06Q 30/0283 (2013.01) [G06N 20/00 (2019.01); G06Q 40/08 (2013.01); G06T 7/0002 (2013.01); G06T 7/13 (2017.01); G06T 7/62 (2017.01)] 20 Claims
OG exemplary drawing
 
1. A computing platform, comprising:
at least one processor;
a communication interface commutatively coupled to the at least one processor; and
memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
receive at least one image;
execute an image analysis operation causing an image analysis and device control system to generate an object dimension output by at least:
determining a plurality of bounding boxes comprising the at least one image, wherein at least some of the plurality of bounding boxes have dimensions that match predetermined dimensions for a neural network;
reducing image quality of the plurality of bounding boxes;
transposing the plurality of bounding boxes on top of a black image that comprises the predetermined dimensions for the neural network; and
determining a pixel dimension for each bounding box of the plurality of bounding boxes;
causing an object prediction control platform to:
determine source data corresponding to the at least one image and a user, and
determine a predicted object output by inputting the source data into one or more machine learning models to output the predicted object output, and wherein determining the predicted object output comprises:
determining, based on a room type corresponding to the at least one image, objects predicted to be in a room,
identifying a correlation between each of the objects predicted to be in the room and the source data, and
in response to determining that a particular correlation exceeds a predetermined threshold, adding the corresponding objects predicted to be in the room to the predicted object output.