Multimodal data learning method and device

    公开(公告)号:US11651214B2

    公开(公告)日:2023-05-16

    申请号:US16764677

    申请日:2018-11-13

    CPC classification number: G06N3/08 G06F18/217 G06N3/045 G06N20/20

    Abstract: An artificial intelligence (AI) system capable of simulating functions of a human brain, such as recognition and judgment, by using the machine learning algorithm such as deep learning, and an application thereof are provided. A method of learning multi-modal data according to the AI system and an application thereof includes: obtaining first context information representing a characteristic of a first signal and second context information representing a characteristic of a second signal by using a first learning network model; obtaining hidden layer information based on the first context information and the second context information by using a second learning network model; obtaining a correlation value representing a relation degree between the hidden layer information by using the second learning network model; and learning the hidden layer information in which the correlation value is derived as a maximum value.

    NEURON CIRCUIT WITH ONE BIRISTOR AND TWO TRANSISTORS, AND DEVICES INCLUDING THE SAME

    公开(公告)号:US20230142820A1

    公开(公告)日:2023-05-11

    申请号:US17969006

    申请日:2022-10-19

    CPC classification number: G06N3/063

    Abstract: According to an embodiment of the present disclosure, a neuron circuit may be provided. The neuron circuit includes a biristor that includes a collector electrode receiving a constant input current from a first synapse circuit and an emitter electrode connected with a ground and outputs a collector signal through the collector electrode, and a voltage divider that is enabled by the collector signal, performs voltage division on an operating voltage by using values of resistances included therein, and outputs an output voltage corresponding to a result of the voltage division to a second synapse circuit.

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