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公开(公告)号：US20220335711A1
公开(公告)日：2022-10-20
申请号：US17853633
申请日：2022-06-29
Inventor： Teng XI , Gang ZHANG
IPC: G06V10/776 , G06V10/80 , G06V10/774 , G06V10/82
Abstract: A method for generating a pre-trained model, includes: extracting, by each of candidate models that are selected from a model set, features from samples in a test set, to obtain features output by each of the candidate models; obtaining fusion features by fusing features output by the candidate models; obtaining prediction information by performing a preset target recognition task based on the fusion features; determining combination performance of the candidate models based on difference between the prediction information and standard information of the samples; and generating the pre-trained model based on the candidate models in response to the combination performance satisfying a preset performance index.
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公开(公告)号：US20240265687A1
公开(公告)日：2024-08-08
申请号：US18020396
申请日：2022-04-22
Inventor： Bi LI , Nan PENG , Teng XI , Gang ZHANG
CPC classification number: G06V10/806 , G06V10/7715
Abstract: A method of fusing an image feature, an electronic device, and a storage medium are provided, which relate to the field of artificial intelligence, in particular to fields of computer vision and depth learning, and may be applied to scenarios such as image processing and image recognition. The method includes: inputting an image into a first image processing model among N serially connected image processing models, to obtain an output feature of the first image processing model, an i-th image processing model includes a first shared layer to an i-th shared layer, i=1, . . . , N, and N is a natural number greater than or equal to 2; inputting an output feature of a j-th image processing model into a (j+1)-th image processing model, to obtain an output feature of the (j+1)-th image processing model, j=1, . . . , N−1; and fusing the output features of the N image processing models.
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Patent Agency Ranking
公开(公告)号：US20230145853A1
公开(公告)日：2023-05-11
申请号：US17980095
申请日：2022-11-03
Inventor： Teng XI , Gang ZHANG
CPC classification number: G06N3/08 , G06K9/6262
Abstract: A method of generating a pre-training model, an electronic device, and a storage medium, which relate to a field of an artificial intelligence technology, in particular to a field of a computer vision and deep learning technology. The method includes: determining, for each of a plurality of tasks, a performance index set corresponding to a candidate model structure set, the candidate model structure set is determined from a plurality of model structures included in a search space, and the search space is a super-network-based search space; determining, from the candidate model structure set, a target model structure according to a plurality of performance index sets, the target model structure is a model structure meeting a performance index condition, and the plurality of performance index sets correspond to the plurality of tasks respectively; and determining the target model structure as the pre-training model.
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公开(公告)号：US20240303962A1
公开(公告)日：2024-09-12
申请号：US18020914
申请日：2022-04-22
Inventor： Bi LI , Nan PENG , Teng XI , Gang ZHANG
Abstract: A method of determining an image feature, an electronic device, and a storage medium are provided, which relate to the field of artificial intelligence technology, in particular to fields of computer vision and depth learning technology, and may be applied to scenarios such as image processing and image recognition. The method includes: dividing an original image into a plurality of local images as an image to be processed, and each local image includes a plurality of image blocks; determining a local feature of the image to be processed according to a relationship between each image block in each local image; and determining a global feature of the image to be processed according to a relationship between a first image block at a preset position in a local image and one or more second image blocks at the preset position in other local images of the plurality of local images.
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公开(公告)号：US20230049458A1
公开(公告)日：2023-02-16
申请号：US17980970
申请日：2022-11-04
Inventor： Teng XI , Gang ZHANG
Abstract: A method of generating a pre-training model, an electronic device and a storage medium, which relate to a field of an artificial intelligence technology, in particular to a computer vision and deep learning technology. The method includes: determining a performance index set corresponding to a candidate model structure set, the candidate model structure set is determined from a plurality of model structures included in a search space, and the search space is a super-network-based search space; determining, from the candidate model structure set, a target model structure corresponding to each chip according to the performance index set, each target model structure is a model structure meeting a performance index condition; and determining, for each chip, the target model structure corresponding to the chip as a pre-training model corresponding to the chip, the chip is configured to run the pre-training model corresponding to the chip.
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6.发明公开公开(公告)号：US20230186607A1
公开(公告)日：2023-06-15
申请号：US18148174
申请日：2022-12-29
Inventor： Nan PENG , Bi LI , Teng XI , Gang ZHANG
IPC: G06V10/771 , G06V10/774 , G06V10/72 , G06V10/77
CPC classification number: G06V10/771 , G06V10/774 , G06V10/72 , G06V10/7715
Abstract: A multi-task identification method, a training method, an electronic device, and a storage medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of deep learning, image processing and computer vision technologies, and may be applied to scenarios such as human faces. A specific implementation solution includes: obtaining first intermediate feature data according to an image to be identified; selecting a feature extraction strategy having a greatest matching degree with the image to be identified from a plurality of feature extraction strategies based on a target selection strategy and the first intermediate feature data, so as to obtain a target feature extraction strategy; processing the first intermediate feature data based on the target feature extraction strategy, to obtain second intermediate feature data; and obtaining a multi-task identification result for the image to be identified according to the second intermediate feature data.
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公开(公告)号：US20230147202A1
公开(公告)日：2023-05-11
申请号：US18153292
申请日：2023-01-11
Inventor： Bi LI , Nan PENG , Teng XI , Gang ZHANG
CPC classification number: G06V40/172 , G06V40/171 , G06V10/806 , G06V10/751
Abstract: A method for face recognition is disclosed. The method includes: obtaining an image to be recognized; extracting an image feature of the image to be recognized; obtaining a fused feature corresponding to a reference image of reference image; determining a similarity between the image feature of the image to be recognized and the fused feature corresponding to the reference image of the reference images to obtain a determination result of the similarity; and determining, based on the obtained determination result of the similarity, a face recognition result of the image to be recognized. It can be learned that recognition precision of a human face having a shielding object and a human face not having the shielding object may be ensured by means of this solution.
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