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1.发明公开公开(公告)号：US20230146519A1
公开(公告)日：2023-05-11
申请号：US18148904
申请日：2022-12-30
Inventor： Minlong Peng , Mingming Sun , Ping Li
IPC: G06F40/30
CPC classification number: G06F40/30
Abstract: The present disclosure provides a method for selecting an annotated sample. The method includes: determining a first attribute and a second attribute of a sample characteristic; in which the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set; and determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute; in which the target annotated sample is configured to train a classification model, the classification model includes a model for determining an emotion polarity by analyzing an input sample to be classified.
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公开(公告)号：US20230133218A1
公开(公告)日：2023-05-04
申请号：US18148812
申请日：2022-12-30
Inventor： Jingyi Yang , Tan Yu , Mingming Sun , Ping Li
Abstract: An image segmentation method includes: obtaining an image to be segmented containing a target object; performing at least one image feature fusion processing on associated feature points based on the image to be segmented, and extracting global feature information during each image feature fusion processing, wherein the associated feature points are at least two feature points having a location association relation; and determining, based on the global feature information extracted, a segmentation mask for the target object.
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公开(公告)号：US11947552B2
公开(公告)日：2024-04-02
申请号：US17947659
申请日：2022-09-19
Inventor： Xu Li , Yunfeng Cai , Mingming Sun , Ping Li
IPC: G06F17/00 , G06F16/22 , G06F16/2458
CPC classification number: G06F16/2465 , G06F16/2237
Abstract: A method for discovering causality from data includes acquiring to-be-processed data, and obtaining a covariance matrix of the to-be-processed data; determining a first target column in the covariance matrix, taking the number of columns of the first target column as a first place in a rearrangement sequence, and obtaining a first upper triangular matrix according to the first target column; determining a position of the number of columns of the covariance matrix other than the first target column except the first place in the rearrangement sequence according to the first target column and the first upper triangular matrix, and obtaining an upper triangular matrix in each position determination; obtaining an adjacency matrix according to an upper triangular matrix and a rearrangement sequence obtained in final position determination; and generating directed acyclic graph (DAG) by using the adjacency matrix, and taking the DAG as causality discovery result of the to-be-processed data.
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公开(公告)号：US11907668B2
公开(公告)日：2024-02-20
申请号：US18148904
申请日：2022-12-30
Inventor： Minlong Peng , Mingming Sun , Ping Li
Abstract: The present disclosure provides a method for selecting an annotated sample. The method includes: determining a first attribute and a second attribute of a sample characteristic; in which the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set; and determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute; in which the target annotated sample is configured to train a classification model, the classification model includes a model for determining an emotion polarity by analyzing an input sample to be classified.
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