CLASSIFICATION OF SUBJECT-INDEPENDENT EMOTION FACTORS

    公开(公告)号:US20210312296A1

    公开(公告)日:2021-10-07

    申请号:US17259966

    申请日:2018-11-09

    Abstract: A method of removing individual variation from emotional representations may include classifying physiological data based on subject-independent emotion factors. The subject-independent emotion factors are isolated from subject-dependent individual factors. Further, a non-transitory computer readable medium includes computer usable program code embodied therewith. The computer usable program code, when executed by the processor classifies, with a first neural network, the physiological data based on subject-independent emotion factors from the trained first neural network. The subject-independent emotion factors have been isolated within the physiological data from subject-dependent individual factors.

    Determinations of Characteristics from Biometric Signals

    公开(公告)号:US20230274186A1

    公开(公告)日:2023-08-31

    申请号:US18043321

    申请日:2020-09-08

    CPC classification number: G06N20/00 G06F3/015

    Abstract: An example system includes a plurality of biometric sensors. The system also includes a first classifier engine to produce a first latent space representation of a first signal from a first biometric sensor of the plurality of biometric sensors. The system includes a second classifier engine to produce a second latent space representation of a second signal from a second biometric sensor of the plurality of biometric sensors. The system includes an attention engine to weight the first latent space representation and the second latent space representation based on correlation among latent space representations. The system includes a final classifier engine to determine a characteristic of a user based on the weighted first and second latent space representations.

    Determinations of Characteristics from Biometric Signals

    公开(公告)号:US20230273682A1

    公开(公告)日:2023-08-31

    申请号:US18043316

    申请日:2020-09-08

    CPC classification number: G06F3/015

    Abstract: An example system includes a plurality of biometric sensors to generate a plurality of signals. The system includes a feature engine to generate a plurality of feature vectors from the plurality of signals. The system includes a classifier engine to generate a plurality of decision vectors based on the plurality of feature vectors. The system includes an attention engine to weight the plurality of feature vectors and the plurality of decision vectors and determine a characteristic of a user based on the weighted feature and decision vectors.

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