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公开(公告)号：US20210097101A1
公开(公告)日：2021-04-01
申请号：US16975631
申请日：2019-09-27
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Fengshuo HU , Honghong JIA
IPC: G06F16/532 , G06K9/32 , G06K9/00 , G06F16/583
Abstract: Embodiments of the present disclosure provide a method and an apparatus for searching for an image and a related storage medium. The method includes obtaining reference keypoint data of a reference person in a reference image, and searching, based on the reference keypoint data, a set of candidate images for at least one target image containing at least one candidate person that has a pose similar to the reference person.
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公开(公告)号：US20200210707A1
公开(公告)日：2020-07-02
申请号：US16537565
申请日：2019-08-10
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Honghong JIA , Jibo ZHAO
Abstract: A sample extraction method targeting a video classification problem includes acquiring video data, parsing the video data to obtain a plurality of consecutive single-frame images corresponding to the video data, and extracting feature images from the plurality of consecutive single-frame images to compose samples, where the feature images are used to summarize content information of the video data, and the samples do not contain redundant image data.
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公开(公告)号：US20210159451A1
公开(公告)日：2021-05-27
申请号：US16643720
申请日：2019-05-21
Inventor： Yanzhen CUI , Jin HAN , Honghong JIA , Lijin ZHAO , Xiaojun GU
Abstract: The present disclosure provides an OLED display substrate, a method for preparing the same, and a display device. The OLED display substrate includes an OLED device located on a base substrate and a packaging unit covering the OLED device. The packaging unit includes an inorganic material layer, an organic material layer, and a fluorine-doped diamond-like carbon layer located between the inorganic material layer and the organic material layer.
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Patent Agency Ranking
公开(公告)号：US20230252821A1
公开(公告)日：2023-08-10
申请号：US17610148
申请日：2021-01-26
Applicant: BOE Technology Group Co., Ltd.
Inventor： Honghong JIA , Fengshuo HU , Jingru WANG
CPC classification number: G06V40/172 , G06V40/20 , G06V10/7715 , G06V10/751
Abstract: Provided is a control method including obtaining a first image; performing face recognition and gesture recognition on the first image; turning on a gesture control function when a first target face is recognized from the first image and a first target gesture is recognized from the first image; and returning to the act of obtaining the first image when the first target face is not recognized from the first image or the first target gesture is not recognized from the first image.
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5.发明申请公开(公告)号：US20220365670A1
公开(公告)日：2022-11-17
申请号：US17763704
申请日：2021-03-12
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Honghong JIA , Fengshuo HU
IPC: G06F3/04883 , G06F3/0354 , G06K9/62
Abstract: A handwriting processing method, a handwriting processing device and a non-transitory storage medium. The handwriting processing method includes: acquiring a handwriting point group corresponding to a stroke on a working surface of a touch device, the handwriting point group including a plurality of handwriting points arranged in sequence, and data of each handwriting point in the plurality of handwriting points including a coordinate and an action type, determining a plurality of model patterns corresponding to the plurality of handwriting points of model patterns being in one-to-one correspondence with the plurality of handwriting points; and sequentially connecting the plurality of model patterns, to determine a handwriting track for displaying corresponding to the handwriting point group.
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公开(公告)号：US20220357843A1
公开(公告)日：2022-11-10
申请号：US17763181
申请日：2021-04-29
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Honghong JIA , Rui ZHENG , Ruibin XUE
IPC: G06F3/04883 , G06V30/32 , G06F3/0354 , G06F3/041
Abstract: A handwriting processing method, a touch display device, a computer device, and a storage medium are provided. The handwriting processing method includes: determining, according to a sample point in a writing track that is input by a user by means of a touch display, a group of track points and a related parameter of each track point, the related parameter including a coordinate parameter and a time parameter; determining, according to the related parameter of each track point, a start position, an end position, and a type of a stroke contained in the writing track, where the type of the stroke includes one of a horizontal stroke, a vertical stroke, a left-falling stroke, a right-falling stroke or a lifting stroke; and determining, according to the type of the stroke, a shape of the start position of the stroke.
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公开(公告)号：US20200293786A1
公开(公告)日：2020-09-17
申请号：US16523124
申请日：2019-07-26
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Honghong JIA , Yanzhen CUI
Abstract: The present disclosure provides a video identification method, a video identification device and a storage medium. The video identification device extracts an image and an optical flow from a video, classifies the image by using a first machine learning model to obtain a first classification result, classifies the optical flow by using a second machine learning model to obtain a second classification result, wherein a depth of the first machine learning model is larger than a depth of the second machine learning model, and fuses the first classification result and the second classification result to obtain the identification result of the video.
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公开(公告)号：US20200210708A1
公开(公告)日：2020-07-02
申请号：US16542209
申请日：2019-08-15
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Honghong JIA , Jibo ZHAO
Abstract: A method for video classification includes: extracting an original image and an optical flow image corresponding to a to-be-classified video from the to-be-classified video; inputting the original image to a space-domain convolutional neural network model to obtain a space-domain classification result corresponding to the to-be-classified video; inputting the optical flow image to a time-domain convolutional neural network model to obtain a time-domain classification result corresponding to the to-be-categorized video, wherein the time-domain convolutional neural network model and the space-domain convolutional neural network model are convolutional neural network models of different network architectures; and merging the space-domain classification result and the time-domain classification result to obtain a classification result corresponding to the to-be-classified video.
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