MULTI-AGENT INFERENCE
    2.
    发明申请

    公开(公告)号:US20220383149A1

    公开(公告)日:2022-12-01

    申请号:US17330099

    申请日:2021-05-25

    Abstract: A computer-implemented method includes determining, by a master node, model update information at least based on a workload related to a task and a resource capacity of a computing environment. The model update information indicates respective model update suggestions for a plurality of inference models configured to perform the task. The method further includes distributing, by the master node, the model update information to a plurality of inference agents in the computing environment. The plurality of inference agents has a plurality of instances of the plurality of inference models executed thereon.

    Weight matrix prediction
    3.
    发明授权

    公开(公告)号:US11748617B2

    公开(公告)日:2023-09-05

    申请号:US17016503

    申请日:2020-09-10

    CPC classification number: G06N3/08 G06F18/217 G06F18/25 G06F18/285

    Abstract: Embodiments of the present disclosure relate to weight matrix prediction. In an embodiment, a computer-implemented method is disclosed. The method comprises sending a candidate weight matrix of a neural network to one of a plurality of computing nodes comprised in a computing system to perform a testing iteration. The method further comprises receiving a testing loss value from the one of the plurality of computing nodes based on the testing iteration. The method further comprises evaluating whether the testing loss value is applicable. The method further comprises determining that the candidate weight matrix is available to be employed in a new formal iteration in response to the testing loss value being applicable. In other embodiments, a system and a computer program product are disclosed.

    INFERENCE MODEL OPTIMIZATION
    4.
    发明申请

    公开(公告)号:US20220188676A1

    公开(公告)日:2022-06-16

    申请号:US17122774

    申请日:2020-12-15

    Abstract: An approach to optimize performance for large scale inference models. Data in the form of images is received from sensors such as cameras. The data is processed to generate data tags associated with the context of the image and portion the images. Model tags are generated based on data characteristics or user input. The tags and their associated data are added to a time-based queue for delivery to the appropriate inference models. Based on the embedded delivery time and frequency, the portioned images are delivered to the appropriate inference models.

    Multistage process model training

    公开(公告)号:US11348213B2

    公开(公告)日:2022-05-31

    申请号:US16788334

    申请日:2020-02-12

    Abstract: Techniques for multistage process model training are described herein. Another aspect includes determining a first gray level histogram corresponding to a first input image. Another aspect includes determining a second gray level histogram corresponding to a second input image. Another aspect includes determining a set of change values, each change value corresponding to a change in a respective gray level from the first gray level histogram to the second gray level histogram. Another aspect includes comparing each change value of the set of change values to a threshold. Another aspect includes, based on determining that a first change value of the set of change values is higher than the threshold, adding a first gray level corresponding to the first change value to a hot zone of the second input image. Another aspect includes training a model using the hot zone of the second input image.

    WEIGHT MATRIX PREDICTION
    6.
    发明申请

    公开(公告)号:US20220076113A1

    公开(公告)日:2022-03-10

    申请号:US17016503

    申请日:2020-09-10

    Abstract: Embodiments of the present disclosure relate to weight matrix prediction. In an embodiment, a computer-implemented method is disclosed. The method comprises sending a candidate weight matrix of a neural network to one of a plurality of computing nodes comprised in a computing system to perform a testing iteration. The method further comprises receiving a testing loss value from the one of the plurality of computing nodes based on the testing iteration. The method further comprises evaluating whether the testing loss value is applicable. The method further comprises determining that the candidate weight matrix is available to be employed in a new formal iteration in response to the testing loss value being applicable. In other embodiments, a system and a computer program product are disclosed.

    MULTISTAGE PROCESS MODEL TRAINING

    公开(公告)号:US20210248726A1

    公开(公告)日:2021-08-12

    申请号:US16788334

    申请日:2020-02-12

    Abstract: Techniques for multistage process model training are described herein. Another aspect includes determining a first gray level histogram corresponding to a first input image. Another aspect includes determining a second gray level histogram corresponding to a second input image. Another aspect includes determining a set of change values, each change value corresponding to a change in a respective gray level from the first gray level histogram to the second gray level histogram. Another aspect includes comparing each change value of the set of change values to a threshold. Another aspect includes, based on determining that a first change value of the set of change values is higher than the threshold, adding a first gray level corresponding to the first change value to a hot zone of the second input image. Another aspect includes training a model using the hot zone of the second input image.

    PATH PLANNING
    10.
    发明申请

    公开(公告)号:US20230036851A1

    公开(公告)日:2023-02-02

    申请号:US17386003

    申请日:2021-07-27

    Abstract: The present invention provides a computer-implemented method, a system, and a computer program product for path planning According to the computer-implemented method, a target discriminator is selected from a set of discriminators with different kernel sizes based on a target image obtained from an image capturing device. In this case, a confidence of the target image is determined using the target discriminator. The confidence indicates whether the target image contains a target object to be captured. Thereby, a movement indication for moving the image capturing device to capture the target object is determined based on the confidence of the target image.

Patent Agency Ranking