Method and System for Identifying Objects
    171.
    发明公开

    公开(公告)号:US20230360380A1

    公开(公告)日:2023-11-09

    申请号:US18044443

    申请日:2020-09-11

    Abstract: The present disclosure provides methods and/or systems for identifying an object. An example method includes: generating a plurality of synthesized images according to a three-dimensional digital model, the plurality of synthesized images having different view angles; respectively extracting eigenvectors of the plurality of synthesized images; generating a first fused vector by fusing the eigenvectors of the plurality of synthesized images; inputting the first fused vector into a classifier to train the classifier; acquiring a plurality of pictures of the object, the plurality of pictures respectively having same view angles as at least a portion of the plurality of synthesized images; respectively extracting eigenvectors of the plurality of pictures; generating a second fused vector by fusing the eigenvectors of the plurality of pictures; and inputting the second fused vector into the trained classifier to obtain a classification result of the object.

    METHOD AND DEVICE FOR TRAINING A NEURAL NETWORK

    公开(公告)号:US20230351741A1

    公开(公告)日:2023-11-02

    申请号:US18302230

    申请日:2023-04-18

    Abstract: A computer-implemented method for training a machine learning system for transferring images of a source domain into a target domain. The method includes: ascertaining source patches based on source images of a source domain and target patches based on target images of a target domain, the source patches and the target patches each being assigned pixel-by-pixel pieces of meta-information; ascertaining tuples, each including one source patch and at least one target patch which characterizes a neighbor of the source patch nearest to k according to a similarity measure, k being a hyperparameter of the method and the similarity measure characterizing a similarity between a source patch and a target patch based on the pixel-by-pixel meta-information of the source patch and of the target patch; training the machine learning system based on the source patches of the tuples and on the target patches of the tuples.

    SYSTEM AND METHOD FOR MONITORING, IDENTIFYING LOCATION AND DIRECTION OF IMPACT EVENTS IN REAL-TIME

    公开(公告)号:US20230343141A1

    公开(公告)日:2023-10-26

    申请号:US18136397

    申请日:2023-04-19

    CPC classification number: G06V40/23 G06V20/44 G06V2201/07

    Abstract: A system for identifying location and direction of impact events in real-time comprises an impact event monitoring device includes multiple sensors, a processing device, and a memory unit. The sensors and the memory unit are electrically coupled to the processing device. The sensors configured to measure impact parameters, the impact parameters include quaternions, Euler angles, vital statistics, rotational angle of the head of the individual and the object, motion of the individual and the object, gyroscope vectors, and velocity. The measured impact parameters are transmitted to the processing device and is configured to analyze measured impact parameters and create impact data of impact events, second computing device includes an impact event reporting module. The impact event reporting module configured to receive the impact data of the impact events from the processing device thereby enabling an emergency service provider to determine severity of impact events to provide better treatment to the individual.

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