公开(公告)号：US20240265595A1

公开(公告)日：2024-08-08

申请号：US18565364

申请日：2021-12-28

Applicant: BOE Technology Group Co., Ltd.

Inventor： Lifei ZHAO ,  Jiahui BIAN ,  Jinpeng WANG ,  Xin LIU ,  Guangwei HUANG ,  Fanhao KONG ,  Fengshuo HU ,  Zhanfu AN

IPC: G06T11/20 ,  G06F3/04883 ,  G06F40/177

CPC classification number: G06T11/206 ,  G06F3/04883 ,  G06F40/177

Abstract: Provided are a display device and a method for displaying a chart, the display device including: a display screen and a control circuit. The control circuit includes a processor and a memory; the memory is used for storing a program executable by the processor; and the processor is used for reading the program in the memory and performing the following steps: identifying writing track information in a display area of the display screen to obtain a data identification result; in response to a user's chart drawing instruction, determining a chart type corresponding to the chart drawing instruction; and in response to the user's chart drawing instruction, drawing, according to the data identification result, a chart of the chart type corresponding to the chart drawing instruction, and displaying the drawn chart in the display area.

公开(公告)号：US20220300767A1

公开(公告)日：2022-09-22

申请号：US17555167

申请日：2021-12-17

Applicant: BOE Technology Group Co., Ltd.

Inventor： Zhanfu AN

IPC: G06K9/62 ,  G06V20/70 ,  G06V10/42 ,  G06V10/82 ,  G06N3/08

Abstract: The present application disclose a neural network of predicting image definition, a training method and a prediction method. The training method includes: obtaining an image set and definition labels of some images in the image set, thereby obtaining image samples with the definition labels and to-be-expanded images except for the image samples; and extracting definition features of at least some images in the image set, obtaining definition labels of at least some images in the to-be-expanded images according to the extracted definition features, correcting the definition labels of the at least some images in the to-be-expanded images to expand the image samples, and using the image samples to train the neural network of predicting image definition, thereby obtaining a trained neural network.

公开(公告)号：US20240242488A1

公开(公告)日：2024-07-18

申请号：US17915489

申请日：2021-10-28

Applicant: BOE Technology Group Co., Ltd.

Inventor： Zeyu SHANGGUAN ,  Zhanfu AN ,  Fanhao KONG

IPC: G06V10/776 ,  G06V10/25 ,  G06V10/44 ,  G06V10/82 ,  G06V20/70

CPC classification number: G06V10/776 ,  G06V10/25 ,  G06V10/44 ,  G06V10/82 ,  G06V20/70 ,  G06V2201/07

Abstract: Provided is a method for training a target detection model. The method includes: determining a first region in a sample image, wherein the first region is a target region predicted by the target detection model in the sample image; determining a relationship between an intersection region and the first region, wherein the intersection region is an intersection of the first region and a second region, wherein the second region is a region annotated for a target in the sample image in a data annotation phase, and surrounds the target in the sample image; determining, in response to the relationship between the intersection region and the first region satisfying a target relationship, a predetermined low loss function value as a loss function value of the first region, wherein the predetermined low loss function value is a constant; and training the target detection model with reference to the loss function value.

公开(公告)号：US20240185590A1

公开(公告)日：2024-06-06

申请号：US17797034

申请日：2021-05-31

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Rui ZHENG ,  Xiaojun TANG ,  Zhanfu AN ,  Guangwei HUANG

IPC: G06V10/82 ,  G06V10/77 ,  G06V10/80

CPC classification number: G06V10/82 ,  G06V10/7715 ,  G06V10/806

Abstract: A method for training an object detection model includes: firstly obtaining M sample image sets; then, obtaining an initial object detection model; and finally, training the initial object detection model by using the M sample image sets to obtain the object detection model. A sample image set includes at least one sample image and object type(s) of object(s) in each sample image. An object type corresponds to one sample image set, and the M sample image sets correspond to N object types.

公开(公告)号：US20250131179A1

公开(公告)日：2025-04-24

申请号：US18690543

申请日：2022-02-28

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Lifei ZHAO ,  Tieli CHEN ,  Jiahui BIAN ,  Pengyu LIU ,  Fengshuo HU ,  Guangwei HUANG ,  Zhanfu AN ,  Yuhan QIN ,  Chao NIE ,  Cheng MA

IPC: G06F40/103 ,  G06F3/04842 ,  G06F3/0488

Abstract: A display system, a method for processing a trajectory point sequence, a storage medium, and a device are provided. The display system includes a display, a processor, and an input component. The processor is configured to control the display to display an interaction interface; receive a trajectory point sequence input by a user by means of the input component; generate a first content based on the trajectory point sequence and control the display to display the first content; recognize a first identification sequence included in the trajectory point sequence, to determine a first feature identifier corresponding to the first content; determine a cluster relationship of the first content according to the first feature identifier; generate a display region in a preset format according to the cluster relationship; and control the display to display the display region on the interaction interface.

公开(公告)号：US20240249547A1

公开(公告)日：2024-07-25

申请号：US18005379

申请日：2021-11-12

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Tingting WANG ,  Zhanfu AN

IPC: G06V40/10 ,  G06V10/44 ,  G06V10/77 ,  G06V10/771 ,  G06V10/774 ,  G06V10/80 ,  G06V10/82

CPC classification number: G06V40/10 ,  G06V10/44 ,  G06V10/771 ,  G06V10/7715 ,  G06V10/774 ,  G06V10/806 ,  G06V10/82

Abstract: A pedestrian attribute recognition method based on a pedestrian attribute recognition system is provided, and the system includes at least one attribute localization module. Each attribute localization module corresponds to a plurality of pedestrian attributes; and the attribute localization module includes a spatial transformation unit and an attribute recognition unit. The method includes: extracting, by the spatial transformation unit, feature information in a discriminable region from feature information input into the spatial transformation unit, and the discriminable region being related to the plurality of pedestrian attributes corresponding to the attribute localization module; and outputting, by the attribute recognition unit, recognition results of the plurality of pedestrian attributes corresponding to the attribute localization module according to the feature information in the discriminable region.

公开(公告)号：US20240242540A1

公开(公告)日：2024-07-18

申请号：US18562336

申请日：2023-01-04

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Xianbin LIU ,  Fanhao KONG ,  Zhanfu AN ,  Zeyu SHANGGUAN

IPC: G06V40/20 ,  G06V10/26 ,  G06V10/74 ,  G06V10/764 ,  G06V10/774 ,  G06V20/40

CPC classification number: G06V40/20 ,  G06V10/267 ,  G06V10/273 ,  G06V10/761 ,  G06V10/764 ,  G06V10/774 ,  G06V20/41

Abstract: An action recognition method includes: an electronic device sampling a plurality of image frames of a video to be recognized, and according to the plurality of image frames and a pre-trained self-attention model, determining a probability distribution of the video to be recognized being similar to a plurality of action categories; further, based on the probability distribution of the video to be recognized being similar to the plurality of action categories, the electronic device determining, from the plurality of action categories, an action category having a probability greater than or equal to a preset threshold as a target action category corresponding to the video to be recognized.