Abstract: The present disclosure relates to a method for state estimation of a target comprising: obtaining an observation variable of the target at different moments through a plurality of sensors, wherein at least one observation variable is acquired by each sensor; determining a state variable of the target at different moments based on the observation variable; and optimizing the state variable of the target by minimizing a loss function. The loss function includes at least one of a position loss, an orientation loss, a velocity loss, a size loss, or a structural constraint of the target. The method of the present disclosure may obtain a sufficiently accurate state estimate. In addition, an apparatus, an electronic device, and a medium for state estimation of the target are also provided.

Abstract: The present disclosure relates to a method for target state estimation comprising: acquiring a data frame sequence corresponding to a plurality of moments; determining a first time window based on the data frame sequence, the first time window comprising a first set of state variables to be optimized; determining a plurality of second time windows within the first time window, wherein the number of data frames in each second time window is less than the number of data frames in the first time window, there is a repeated data frame in two adjacent second time windows, and there is a second set of state variables to be optimized; and optimizing the second set of state variables in the plurality of second time windows to obtain an optimized first set of state variables. The method of the present disclosure may obtain sufficiently accurate state estimation.

Abstract: A method (100) for diagnosing a subject with cancer using a cancer diagnosis system (200), comprising: receiving (120), from an electronic health record database, a plurality of medical records for a subject; analyzing (130), by a trained cancer diagnosis model (263) of the system, the received plurality of medical records for the subject; generating (140), by the analysis, a cancer diagnosis for the subject, wherein the cancer diagnosis comprises both an identification of a cancer type and a date of diagnosis; and providing (150), via a user interface (240) of the system, the generated cancer diagnosis.