System and Method for Closed-Loop Uncertainty for Human-Machine Teamwork

    公开(公告)号:US20250036982A1

    公开(公告)日:2025-01-30

    申请号:US18783788

    申请日:2024-07-25

    Abstract: A method that includes receiving user input associated with identifying a threshold point associated with a classification task, identifying, a machine learning model, in the first set of visual data, a machine placement candidate point associated with identifying the threshold point, and identifying, based on the machine placement candidate point, a set of baseline confidence values via a baseline uncertainty model. The method includes training the machine learning model based on a determined state space by identifying, subsequent sets of visual data additional threshold points, receiving user feedback indicating an accuracy, comparing the baseline confidence values with locations associated with the additional threshold points, generating reward values based on an identified amount of error, and configuring the machine learning model based on the reward values. The method includes identifying in a second set of visual data, via the trained machine learning model, a visual feature associated with the classification task.

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