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：US20250095370A1

公开(公告)日：2025-03-20

申请号：US18018712

申请日：2022-02-23

Applicant: BOE Technology Group Co., Ltd.

Inventor： Zeyu SHANGGUAN ,  Hanwen LIU ,  Fanhao KONG

IPC: G06V20/52 ,  G06T3/40 ,  G06V40/10 ,  G06V40/20

Abstract: The present disclosure provides a traffic statistics collection method and apparatus. The method includes: obtaining a first image of a target place; performing body detection on the first image to obtain body detection boxes of respective target objects in the first image, where the body detection boxes indicate body areas of the respective target objects; for each target object of the respective target objects, determining a head detection box of the target object according to the body detection box of the target object, wherein the head detection box indicates a head area of the target object; and obtaining a traffic statistics result of the target place according to head detection boxes of the respective target objects.

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.

公开(公告)号：US20230027040A1

公开(公告)日：2023-01-26

申请号：US17841697

申请日：2022-06-16

Applicant: BOE Technology Group Co., Ltd.

Inventor： Jingru WANG ,  Fanhao KONG

IPC: G06F3/01 ,  G06V40/16 ,  G06V40/20

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.

公开(公告)号：US20250131756A1

公开(公告)日：2025-04-24

申请号：US18695718

申请日：2021-11-23

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Guangwei HUANG ,  Fengshuo HU ,  Yanjiao WANG ,  Dan WANG ,  Xiaoyan HAN ,  Peihuan YANG ,  Fanhao KONG

IPC: G06V30/19 ,  G06V10/82 ,  G06V30/162

Abstract: The text recognition method includes: acquiring a first high-frequency feature map and a first low-frequency feature map of a target image; performing an M-level convolution process on the first high-frequency feature map and the first low-frequency feature map by M cascaded convolution modules to obtain M pairs of target high-frequency feature map and target low-frequency feature map of the target image, where M is a positive integer; merging the M pairs of target high-frequency feature map and target low-frequency feature map to obtain a target feature map of the target image; determining a probability map and a threshold map of the target image based on the target feature map, and calculating a binarization map of the target image based on the probability map and the threshold map; and determining a text area in the target image based on the binarization map, and recognizing text information in the text area.

公开(公告)号：US20250046164A1

公开(公告)日：2025-02-06

申请号：US18580142

申请日：2023-02-28

Applicant: BOE Technology Group Co., Ltd.

Inventor： Ning ZHANG ,  Yu GU ,  Yue LI ,  Xiaozhen JIA ,  Fanhao KONG ,  Xiao CHU

IPC: G08B13/196 ,  G06T7/70

Abstract: Provided are a method and system for interactively searching for a target object and a storage medium. The method includes: obtaining a first interactive instruction from a first terminal; determining a target object corresponding to the first interactive instruction; obtaining target information of the target object; where the target information includes at least one of: a current position of the target object, picture information of the current position, a historical trajectory of the target object, a navigation route, or any combination thereof; sending the target information to the first terminal such that the first terminal displays the target information.

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：US20240153240A1

公开(公告)日：2024-05-09

申请号：US18281685

申请日：2021-11-17

Applicant: BOE Technology Group Co., Ltd.

Inventor： Zeyu SHANGGUAN ,  Tong LIU ,  Guangwei HUANG ,  Fanhao KONG

IPC: G06V10/74 ,  G06T7/90 ,  G06V10/56 ,  G06V10/75 ,  G06V10/764 ,  G06V10/776

CPC classification number: G06V10/761 ,  G06T7/90 ,  G06V10/56 ,  G06V10/751 ,  G06V10/764 ,  G06V10/776 ,  G06T2207/10024 ,  G06T2207/20081

Abstract: The present disclosure provides an image processing method, an apparatus, a computing device, and a medium, which relates to deep learning technology. In the present disclosure, after acquiring the to-be-processed target image, the first similarities between the target image and the first images of categories are determined based on the first feature vector corresponding to the target image and the second feature vectors respectively corresponding to the plurality of first images. Moreover, based on the first color distribution information of the target region in the target image and the second color distribution information of the target regions in the plurality of first images, the second similarities between the target image and the plurality first images are determined, so that the image category to which the target image belongs can be determined jointly based on the first similarities and the second similarities.