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1.
公开(公告)号:US20230319124A1
公开(公告)日:2023-10-05
申请号:US17975677
申请日:2022-10-28
Inventor: Shuo LI , Xuechao WEI , Yonggao FU , Jiabing LENG , Yawen LIU , Mingfa ZHU , Feng HUANG
IPC: H04L65/61 , H04L65/1073
CPC classification number: H04L65/61 , H04L65/1073
Abstract: The present disclosure provides a method and apparatus for processing a streaming media service, an electronic device, and a storage medium, and relates to the technical field of computers, particularly to technical fields such as industrial vision, deep learning, streaming media, and information flow. A specific implementation solution involves: acquiring registration information of an input source, the registration information including process information of a streaming media service process of the input source and streaming media address information of the input source; enabling the streaming media service process according to the process information; and controlling, by using the streaming media address information, the streaming media service process to process streaming media data of the input source.
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2.
公开(公告)号:US20200380899A1
公开(公告)日:2020-12-03
申请号:US16995898
申请日:2020-08-18
Inventor: Yawei WEN , Jiabing LENG , Minghao LIU , Yulin XU , Jiangliang GUO , Xu LI
IPC: G09G3/00 , G01N21/956 , G06N3/02 , G06T7/00
Abstract: The method and apparatus for detecting a peripheral circuit of a display screen provided by the present disclosure receive a quality detection request sent by a console deployed on a production line of the peripheral circuit of the display screen, where the quality detection request includes a peripheral circuit image of the display screen captured by an image capturing device on the production line of the peripheral circuit of the display screen; zoom in or out on the peripheral circuit image of the display screen to obtain an image to be detected a size of which is consistent with an input size requirement of a defect detection model; input the image to be detected into the defect detection model to obtain a defect detection result; and determine quality of the peripheral circuit of the display screen according to the defect detection result.
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公开(公告)号:US20210073973A1
公开(公告)日:2021-03-11
申请号:US16871633
申请日:2020-05-11
Inventor: Jianfa ZOU , Ye SU , Minghao LIU , Lei NIE , Jiabing LENG , Yawei WEN , Tehui HUANG , Yulin XU , Jiangliang GUO , Xu LI
Abstract: Provided are a method and an apparatus for component fault detection based on an image, and a specific implementation is: when it is determined that an image shot by an image pickup apparatus for a component to be tested with a first shooting parameter does not meet a preset condition, adjusting the first shooting parameter to a second shooting parameter; controlling the image pickup apparatus to shoot for the component to be tested with the second shooting parameter to obtain a first image that meets the preset condition; and performing fault detection on the component to be tested according to the first image. The image pickup apparatus can be adjusted in real time, so that the image can be used for fault detection only when meeting the preset condition, thereby the image is kept stable, and the accuracy rate of component fault identification based on an image is improved.
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4.
公开(公告)号:US20200349875A1
公开(公告)日:2020-11-05
申请号:US16936806
申请日:2020-07-23
Inventor: Yawei WEN , Jiabing LENG , Minghao LIU , Yulin XU , Jiangliang GUO , Xu LI
IPC: G09G3/00 , G01N21/956
Abstract: The present disclosure provides a display screen quality detection method, an apparatus, an electronic device and a storage medium, where the method comprises: receiving a quality detection request sent by a console deployed on a display screen production line, where the quality detection request includes a display screen image captured by an image capturing device on the display screen production line, performing image preprocessing on the display screen image, and inputting the preprocessed display screen image into a defect detection model to obtain a defect detection result, where the defect detection model is obtained by training with a historical defect display screen image using a deep convolutional neural network structure and an instance segmentation algorithm, determining, according to the defect detection result, quality of a display screen corresponding to the display screen image. The technical solution has high defect detection accuracy, good system performance, and high business expansion capability.
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