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Abstract

A machine learning method includes: inputting pieces of position data to a machine learning model configured to receive the pieces of position data indicating a position of an object at respective first points in time, and output occupancy data and flow data, the occupancy data indicating occupancy probability of the object at a second point in time, the flow data indicating a velocity vector of the object at the second point in time; generating second ground truth occupancy data by performing a process of expanding an occupancy region of the object on first ground truth occupancy data at the second point in time; calculating a loss parameter, based on the occupancy data, the second ground truth occupancy data, the flow data, and ground truth flow data at the second point in time; and updating the machine learning model, based on the loss parameter.

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First Claim