Mobile 3D imaging system and method

    公开(公告)号:US12117528B2

    公开(公告)日:2024-10-15

    申请号:US17431037

    申请日:2020-02-15

    CPC classification number: G01S17/89

    Abstract: A system and method for object detection in 3-dimensional space uses a ground up model that makes detecting objects faster and more accurate by combining the error correction and object detection, while also using flat planes as a basis for the mathematics. Two or more 3D scanning devices, such as scanning LIDARs, collect a 3D dataset for a field of view (FOV). The FOV is divided into boxes with a small degree of overlap, then each box is processed iteratively to identify features of an object contained within the box. Box size is chosen so that the portion of the object contained within the box can be assumed to be planar. Adjoining boxes are evaluated for shared data points then merged it the form part of the same object.

    SYSTEMS, METHODS, AND APPARATUSES FOR ACCRUING AND REUSING KNOWLEDGE (ARK) FOR SUPERIOR AND ROBUST PERFORMANCE BY A TRAINED AI MODEL FOR USE WITH MEDICAL IMAGE CLASSIFICATION

    公开(公告)号:US20240339200A1

    公开(公告)日:2024-10-10

    申请号:US18627831

    申请日:2024-04-05

    CPC classification number: G16H30/40 G06V10/764 G16H30/20

    Abstract: Exemplary systems include means for receiving medical image data at the system from a plurality of datasets provided via publicly available sources; evaluating the medical image data for the presence of expert notation embedded within the medical image data; determining the expert notations embedded within the medical image data are formatted using inconsistent and heterogeneous labeling across the plurality of datasets; generating an interim AI model by applying a task head classifier to learn the annotations of the expert notations embedded within the medical image data to generate an interim AI model; scaling the interim AI model having the learned annotations of the expert notations embedded therein to additional tasks by applying multi-task heads using cyclical pre-training of the interim AI model trained previously to generate task-specific AI models, with each respective task-specific AI model having differently configured task-specific learning objectives; training a pre-trained AI model specially configured for an application-specific target task by applying task re-visitation training forcing the pre-trained AI model being trained to re-visit all tasks in each round of training and forcing the pre-trained AI model being trained to re-use all accrued knowledge to improve learning by the pre-trained AI model being trained against the current application-specific target task for which the pre-trained AI model is being trained.

    Device for improved hydration during exercise

    公开(公告)号:US12108891B2

    公开(公告)日:2024-10-08

    申请号:US17835618

    申请日:2022-06-08

    Inventor: Joseph Miller

    CPC classification number: A47G19/2272 A47G21/189 F16L55/10

    Abstract: The present invention is directed to a device that can easily deliver water or other sources of hydration from a bottle, directly to a user during exercise without the use of a traditional hydration bladder. The present invention features a hydration device for allowing delivery of a fluid from a container with a cap with a hole. The hydration device may comprise an outer tubing affixed around the hole and an inner tubing disposed within the outer tubing. The inner tubing may extend past both ends of the outer tubing, slide freely within the outer tubing, and extend to the bottom of the container. Both ends of both tubings may be always open. The fluid may be delivered from the container through the inner tubing when suction is applied. Air may be delivered from the outer tubing to the pre-existing container to prevent collapsing of the pre-existing container.

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