US 12,118,769 B1
Machine learning architecture for peer-based image scoring
Elham Saraee, Medford, MA (US); Jehan Hamedi, Wellesley, MA (US); and Zachary Halloran, Franklin, MA (US)
Assigned to VIZIT LABS, INC., Boston, MA (US)
Filed by VIZIT LABS, INC., Boston, MA (US)
Filed on Jun. 24, 2024, as Appl. No. 18/752,622.
Application 16/537,426 is a division of application No. 15/727,044, filed on Oct. 6, 2017, granted, now 10,380,650, issued on Aug. 13, 2019.
Application 18/752,622 is a continuation in part of application No. 18/587,524, filed on Feb. 26, 2024, granted, now 12,020,471.
Application 18/587,524 is a continuation of application No. 18/466,465, filed on Sep. 13, 2023, granted, now 11,915,469, issued on Feb. 27, 2024.
Application 18/466,465 is a continuation of application No. 18/200,102, filed on May 22, 2023, granted, now 11,763,546, issued on Sep. 19, 2023.
Application 18/200,102 is a continuation in part of application No. 17/833,671, filed on Jun. 6, 2022, granted, now 11,804,028, issued on Oct. 31, 2023.
Application 17/833,671 is a continuation of application No. 17/548,341, filed on Dec. 10, 2021, granted, now 11,417,085, issued on Aug. 16, 2022.
Application 17/548,341 is a continuation in part of application No. 16/537,426, filed on Aug. 9, 2019, abandoned.
Claims priority of provisional application 63/348,984, filed on Jun. 3, 2022.
Claims priority of provisional application 62/537,428, filed on Jul. 26, 2017.
Int. Cl. G06V 10/40 (2022.01); G06F 16/438 (2019.01); G06N 3/045 (2023.01); G06V 10/74 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/761 (2022.01) [G06F 16/438 (2019.01); G06N 3/045 (2023.01); G06V 10/40 (2022.01); G06V 10/82 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory, computer-readable medium including instructions which, when executed by one or more processors, cause the one or more processors to:
display, via an interactive graphic user interface (GUI), a first user interface including a target image and a task selection element;
in response to a selection of the task selection element, display, via the interactive GUI, a second user interface including a target audience selection element;
in response to a selection of a target audience using the target audience selection element, display, via the interactive GUI, a third user interface including a benchmark selection element;
in response to a selection of a benchmark using the benchmark selection element:
execute a target audience machine learning model using as input the target image to generate a performance score indicating a performance of the target image for the target audience;
calculate a benchmark score for the target image based on the performance score of the target image and performance scores for the images of the benchmark, the benchmark score indicating a performance of the target image for the target audience relative to the images of the benchmark; and
display, via the interactive GUI, a fourth user interface including the target image and the benchmark score.