TRAFFIC VIOLATION PREDICTION
    2.
    发明公开

    公开(公告)号:US20240355102A1

    公开(公告)日:2024-10-24

    申请号:US18609097

    申请日:2024-03-19

    摘要: Systems and methods for traffic violation prediction. The systems and methods include obtaining a plurality of bounding boxes of road scene categories from an input dataset by employing a pre-trained detection model. A plurality of pseudo-labels of road scene categories for the plurality of bounding boxes can be obtained by employing the pre-trained detection model. A labeled dataset can be obtained by filtering the input dataset for images having the plurality of pseudo-labels and the plurality of bounding boxes. A traffic violation prediction model can be trained with both unlabeled and labeled dataset including the road scene categories obtained from the pre-trained detection model to predict simultaneous traffic violations of one or more riders in a road scene.

    Security device zones
    5.
    发明授权

    公开(公告)号:US12118864B2

    公开(公告)日:2024-10-15

    申请号:US18447843

    申请日:2023-08-10

    申请人: SimpliSafe, Inc.

    摘要: A method is provided. The method includes receiving, from a monitor interface implemented by a first computing device, input specifying a zone within a field of view of an image capture device; storing, in response to reception of the input, a record defining the zone; receiving, from the image capture device, an image acquired within the field of view by the image capture device; and rendering, via a customer interface implemented by a second computing device distinct from the first computing device, the image with a representation of the zone overlaid upon the image.

    Method and system for processing image, device and medium

    公开(公告)号:US12118771B2

    公开(公告)日:2024-10-15

    申请号:US18564457

    申请日:2022-03-29

    摘要: A method and system for processing image, a computer device and a readable storage medium. The method includes: images in an initial dataset are preprocessed to obtain a training dataset (S1); an image segmentation neural network is trained by the training dataset (S2); a last loss function layer of a trained image segmentation neural network is removed to obtain an inference network (S3); the training dataset is inputted into the inference network to obtain a plurality of logical vectors (S4); a check network is trained on a basis of the plurality of the logical vectors, the initial dataset, and a mask of each of the images in the initial dataset (S5); and inference is performed on an image to be processed by the inference network and a trained check network so as to obtain the mask of the image to be processed (S6).

    DIVISION OF IMAGES INTO SEPARATE COLOR LAYERS

    公开(公告)号:US20240331346A1

    公开(公告)日:2024-10-03

    申请号:US18744121

    申请日:2024-06-14

    摘要: A method of the disclosure includes receiving, by a processing device, a document image, dividing the document image into a plurality of patches and determining, for each patch, whether the patch is monochromatic or polychromatic. It further includes clusterizing a plurality of monochromatic patches into a plurality of clusters within a color space, wherein each cluster corresponds to a color layer of a plurality of color layers of the document image, and segmenting each polychromatic patch into a corresponding plurality of monochromatic segments. The method also includes, for each polychromatic patch, associating each monochromatic segment of the corresponding plurality of monochromatic segments with a cluster of the plurality of clusters, and utilizing the plurality of clusters for performing an information extraction task on the document image.