Spectrum allocation method and apparatus

    公开(公告)号:US11825248B2

    公开(公告)日:2023-11-21

    申请号:US17508432

    申请日:2021-10-22

    CPC classification number: H04Q11/0067 H04Q2011/0086

    Abstract: A method includes: obtaining a transmission bandwidth granularity G1 of a target service and an optical-layer spectrum resource of a target fiber channel corresponding to the target service, where the optical-layer spectrum resource includes N consecutive frequency slots, and all of the N consecutive frequency slots have a same spectrum bandwidth; determining a target spectrum slice from the N frequency slots based on the transmission bandwidth granularity G1, where the target spectrum slice includes N1 consecutive frequency slots, and the target spectrum slice includes at least G1 consecutive idle frequency slots; and allocating the G1 consecutive idle frequency slots included in the target spectrum slice to the target service.

    INFORMATION DETECTION METHOD AND MOBILE DEVICE

    公开(公告)号:US20200320317A1

    公开(公告)日:2020-10-08

    申请号:US16906323

    申请日:2020-06-19

    Abstract: A method includes photographing a first picture, the first picture including a signal light at a first intersection; and detecting a signal light status in the first picture by using a first detection model. The first detection model is a detection model corresponding to the first intersection. The first detection model is obtained by a server through training based on signal light pictures corresponding to the first intersection and signal light statuses in the signal light pictures. The signal light statuses in the signal light pictures are obtained through detection by using a general model. The general model is obtained through training based on pictures in a first set and a signal light status in each picture in the first set. The first set includes signal light pictures of a plurality of intersections.

    Spectrum Allocation Method and Apparatus

    公开(公告)号:US20220070559A1

    公开(公告)日:2022-03-03

    申请号:US17508432

    申请日:2021-10-22

    Abstract: A method includes: obtaining a transmission bandwidth granularity G1 of a target service and an optical-layer spectrum resource of a target fiber channel corresponding to the target service, where the optical-layer spectrum resource includes N consecutive frequency slots, and all of the N consecutive frequency slots have a same spectrum bandwidth; determining a target spectrum slice from the N frequency slots based on the transmission bandwidth granularity G1, where the target spectrum slice includes N1 consecutive frequency slots, and the target spectrum slice includes at least G1 consecutive idle frequency slots; and allocating the G1 consecutive idle frequency slots included in the target spectrum slice to the target service.

    Image denoising method and apparatus

    公开(公告)号:US12062158B2

    公开(公告)日:2024-08-13

    申请号:US17462176

    申请日:2021-08-31

    CPC classification number: G06T5/70 G06N3/045 G06T5/50

    Abstract: This application provides an image denoising method and apparatus, and relates to the artificial intelligence field and specifically relates to the computer vision field. The method includes: performing resolution reduction processing on a to-be-processed image to obtain a plurality of images whose resolutions are lower than that of the to-be-processed image; extracting an image feature of a higher-resolution image based on an image feature of a lower-resolution image to obtain an image feature of the to-be-processed image; and performing denoising processing on the to-be-processed image based on the image feature of the to-be-processed image to obtain a denoised image. This application can improve an image denoising effect.

    IMAGE DENOISING METHOD AND APPARATUS

    公开(公告)号:US20210398252A1

    公开(公告)日:2021-12-23

    申请号:US17462176

    申请日:2021-08-31

    Abstract: This application provides an image denoising method and apparatus, and relates to the artificial intelligence field and specifically relates to the computer vision field. The method includes: performing resolution reduction processing on a to-be-processed image to obtain a plurality of images whose resolutions are lower than that of the to-be-processed image; extracting an image feature of a higher-resolution image based on an image feature of a lower-resolution image to obtain an image feature of the to-be-processed image; and performing denoising processing on the to-be-processed image based on the image feature of the to-be-processed image to obtain a denoised image. This application can improve an image denoising effect.

    Scheduling method, scheduler, storage medium, and system

    公开(公告)号:US11190618B2

    公开(公告)日:2021-11-30

    申请号:US17021425

    申请日:2020-09-15

    Abstract: This disclosure provides a scheduling method, a scheduler, a storage medium, and a system, and belongs to the field of communications technologies. The method includes: obtaining an association relationship diagram and data distribution information, where each node in the association relationship diagram indicates one piece of data, and each directed edge is used to indicate an operation request for obtaining, through calculation based on data indicated by a source node, data indicated by a destination node; sequentially positioning, according to a preset node sorting policy, an operation request corresponding to a traversed node to any server in which data indicated by the traversed node is located; and sequentially scheduling at least one operation request indicated by the at least one directed edge to a server to which the at least one operation request is positioned. The method could be used to reduce the cross-node data transmission, and improving calculation efficiency.

    Noise estimation
    8.
    发明授权

    公开(公告)号:US12118695B2

    公开(公告)日:2024-10-15

    申请号:US17480548

    申请日:2021-09-21

    CPC classification number: G06T5/70 G06T2207/20081

    Abstract: One example image processing device is provided. The example image processing device can include at least one processor and one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to estimate noise in an image, the image being represented by a set of pixels and each pixel of the set of pixels having a value associated with it on each of one or more channels, where estimating the noise comprises processing, using a first trained model that detects stochastic noise, data derived from the image to form a first noise estimate, processing, using a second trained model that detects extreme pixel values, data derived from the image to form a second noise estimate, and combining the first and second noise estimates to form an aggregated noise estimate.

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