Driving policies determination
    232.
    发明授权

    公开(公告)号:US11899707B2

    公开(公告)日:2024-02-13

    申请号:US16628744

    申请日:2018-07-09

    Applicant: Cortica Ltd.

    CPC classification number: G06F16/438 G06N20/00

    Abstract: A method for responding to a query is implemented on at least one computing device and includes: receiving at least one query from a user device; determining a context for the at least one query, selecting at least one deep learning network (DLN) of a plurality of DLNs to process the at least one query, where the selecting is based at least on matching the context to the at least one DLN, sending at least a representation of the at least one query and the context to the at least one DLN, receiving at least one response to the at least one query from the at least one DLN, and sending the at least one response to the user device.

    Filming an event by an autonomous robotic system

    公开(公告)号:US11877052B2

    公开(公告)日:2024-01-16

    申请号:US17643159

    申请日:2021-12-07

    Applicant: Cortica Ltd.

    Inventor: Karina Odinaev

    Abstract: A method for filming an event by an autonomous drone, the method may include acquiring, by the autonomous drone, a current set of images of the event; generating signatures of the current set of images to provide current signatures; searching for one or more relevant concept structures out of a group of concept structures; wherein each relevant concept structure comprises at least one signature that matches at least one of first signatures; wherein each concept structure is associated with filming parameters; and determining, at least in part, based on the filming parameters associated with at least one of the one or more relevant concept structures, next filming parameters to be applied during an acquisition of one or more next sets of images.

    SEMI-SUPERVISED LEARNING VIA DIFFERENT MODALITIES

    公开(公告)号:US20230230350A1

    公开(公告)日:2023-07-20

    申请号:US18155707

    申请日:2023-01-17

    Applicant: Cortica Ltd.

    Inventor: Karina Odinaev

    CPC classification number: G06V10/762 G06V10/7784

    Abstract: A method for semi-supervised learning via different modalities, the method may include obtaining a training sensed information units of a first modality that are associated with a certain pattern; obtaining multimodality information units that are untagged; wherein a multimodality information unit comprises a first modality portion and a second modality portion; searching for certain pattern related multimodality information units, wherein a certain pattern related multimodality information unit comprises a first modality portion that is related to the certain pattern; clustering the second portions of the certain pattern related multimodality information units to provide second portion clusters; generating certain pattern identifiers based on the second portion clusters; and responding to the generating of the certain pattern identifiers; wherein the responding comprises at least one out of storing the certain pattern identifiers, transmitting the certain pattern identifiers, and generating notifications to be sent once a signature of a query sensed information unit of the second modality comprises the certain pattern identifier.

    MONITORING POTENTIAL DROPLETS TRANSMISSION BASES INFECTION EVENTS

    公开(公告)号:US20220208393A1

    公开(公告)日:2022-06-30

    申请号:US17646292

    申请日:2021-12-28

    Applicant: Cortica Ltd.

    Inventor: Karina Odinaev

    Abstract: There may be provided a method for monitoring potential droplets transmission bases infection events, the method may include (a) obtaining sensed information gathered during a monitoring period; (b) identifying, based on the sensed information, a main suspected person and one or more ejection events during which potentially infectious droplets were ejected from the main suspected person, wherein the main suspected person is suspected of suffering from an infectious disease; (c) detecting one or more secondary suspected persons; wherein each of the one or more secondary suspected persons was potentially infected due to one or more ejection events; wherein the detecting is based, at least on part, on infection parameters; and (d) responding to the detecting of at least one suspected person out of the main suspected person and the one or more secondary suspected persons, wherein the responding comprises at least one out of generating an alert, transmitting an alert, storing an alert, and updating at least one data structure regarding the at least one suspected person.

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