知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

268 records (took 0.017 seconds)

    Scalable pipeline for machine learning-based base-variant grouping
    1.
    发明授权
    Scalable pipeline for machine learning-based base-variant grouping 有权

    公开(公告)号：US12112520B2

    公开(公告)日：2024-10-08

    申请号：US17589768

    申请日：2022-01-31

    Applicant: Walmart Apollo, LLC

    Inventor： Yanxin Pan ,  Swagata Chakraborty ,  Ekaterina Pirogova

    IPC: G06V10/762 ,  G06N3/045 ,  G06V10/774 ,  G06V10/82

    CPC classification number: G06V10/7625 ,  G06N3/045 ,  G06V10/7747 ,  G06V10/82

    Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: creating an adjacency list for candidate items using a distance threshold; generating graphs of the candidate items in the adjacency list, wherein nodes of the graphs represent the candidate items, and wherein edges of the graphs represent respective predicted variant neighbor links between pairs of the candidate items; determining, using breakdown logic, first graphs of the graphs that exceed a predetermined size; performing divisive hierarchical clustering on each of the first graphs; and identifying recommended variant groups of the candidate item in the nested subclusters of the hierarchy dendrogram below the respective cut-off value. Other embodiments are described.

    Methods and systems for training learning network for medical image analysis
    2.
    发明授权
    Methods and systems for training learning network for medical image analysis 有权

    公开(公告)号：US12094188B2

    公开(公告)日：2024-09-17

    申请号：US17565274

    申请日：2021-12-29

    Applicant: Shenzhen Keya Medical Technology Corporation

    Inventor： Junhuan Li ,  Ruoping Li ,  Ling Hou ,  Pengfei Zhao ,  Yuwei Li ,  Kunlin Cao ,  Qi Song

    IPC: G06V10/774 ,  G06T7/00 ,  G06V10/776 ,  G06V10/82

    CPC classification number: G06V10/7747 ,  G06T7/0012 ,  G06V10/776 ,  G06V10/82 ,  G06T2207/10081 ,  G06T2207/30048

    Abstract: The present disclosure relates to a training method and a training system for training a learning network for medical image analysis. The training method includes: acquiring an original training data set for a learning network with a predetermined structure; performing, by a processor, a pre-training on the learning network using the original training data set to obtain a pre-trained learning network; evaluating, by the processor, the pre-trained learning network to determine whether the pre-trained learning network has an evaluation defect; when the pre-trained learning network has the evaluation defect, performing, by the processor, a data augmentation on the original training data set for the existing evaluation defect; and performing, by the processor, a refined training on the pre-trained learning network using a data augmented training data set. The present disclosure can evaluate and train the learning network in stages, therefore, the complexity of medical image processing is reduced, and the efficiency and accuracy of medical image analysis are improved.

    Systems and methods for progressive learning for machine-learned models to optimize training speed
    4.
    发明授权
    Systems and methods for progressive learning for machine-learned models to optimize training speed 有权

    公开(公告)号：US12062227B2

    公开(公告)日：2024-08-13

    申请号：US17943880

    申请日：2022-09-13

    Applicant: Google LLC

    Inventor： Mingxing Tan ,  Quoc V. Le

    IPC: G06V10/00 ,  G06V10/774 ,  G06V10/776

    CPC classification number: G06V10/7747 ,  G06V10/776

    Abstract: Systems and methods of the present disclosure can include a computer-implemented method for efficient machine-learned model training. The method can include obtaining a plurality of training samples for a machine-learned model. The method can include, for one or more first training iterations, training, based at least in part on a first regularization magnitude configured to control a relative effect of one or more regularization techniques, the machine-learned model using one or more respective first training samples of the plurality of training samples. The method can include, for one or more second training iterations, training, based at least in part on a second regularization magnitude greater than the first regularization magnitude, the machine-learned model using one or more respective second training samples of the plurality of training samples.

    Method, electronic device, and computer program product for generating avatar
    8.
    发明授权
    Method, electronic device, and computer program product for generating avatar 有权

    公开(公告)号：US12014454B2

    公开(公告)日：2024-06-18

    申请号：US17687874

    申请日：2022-03-07

    Applicant: Dell Products L.P.

    Inventor： Zijia Wang ,  Danqing Sha ,  Jiacheng Ni ,  Zhen Jia

    IPC: G06T13/40 ,  G06V10/774 ,  G06V40/16

    CPC classification number: G06T13/40 ,  G06V10/7747 ,  G06V40/174

    Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for generating an avatar. The method includes generating an indication of correlation among image information, audio information, and text information of a video. The method may further include generating, based on the indication of the correlation, a first feature set and a second feature set representing features of a target object in the video, wherein the first feature set represents invariant features of the target object in the video, and the second feature set represents equivariant features of the target object in the video. The method may further include generating the avatar based on the first feature set and the second feature set. With this method, the generated avatar can be made more accurate and vivid with a better effect, while also reducing data annotation cost, improving operation efficiency, and enhancing user experience.

    Image feature visualization method, image feature visualization apparatus, and electronic device
    9.
    发明授权
    Image feature visualization method, image feature visualization apparatus, and electronic device 有权

    公开(公告)号：US11972604B2

    公开(公告)日：2024-04-30

    申请号：US17283199

    申请日：2020-03-11

    Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY

    Inventor： Shuqiang Wang ,  Wen Yu ,  Chenchen Xiao ,  Shengye Hu ,  Yanyan Shen

    IPC: G06V10/82 ,  G06V10/774

    CPC classification number: G06V10/82 ,  G06V10/7747

    Abstract: An image feature visualization method and apparatus, and an electronic device during model training, inputs the real training data with positive samples into a mapping generator to obtain fictitious training data with negative samples. The mapping generator includes a mapping module configured to learn a key feature map that distinguishes the real training data with positive samples/negative samples, and the fictitious training data with negative samples is generated based on the real training data with positive samples and the key feature map. The training data with negative samples is input into a discriminator to obtain a discrimination result. An optimizer optimizes the mapping generator and the discriminator until training is completed. During model application, a target image that is to be processed is input into the mapping generator, and the mapper in the mapping generator extracts features of the target image.

Patent Agency Ranking