公开(公告)号：US11922551B2

公开(公告)日：2024-03-05

申请号：US17047935

申请日：2019-12-19

Applicant: BOE Technology Group Co., Ltd.

Inventor： Dan Zhu ,  Hanwen Liu ,  Pablo Navarrete Michelini

IPC: G06T13/40 ,  G06F3/0482 ,  G06F3/04845 ,  G06F3/04883 ,  G06T7/194 ,  G06T7/70 ,  G06T11/60

CPC classification number: G06T13/40 ,  G06F3/0482 ,  G06F3/04845 ,  G06F3/04883 ,  G06T7/194 ,  G06T7/70 ,  G06T11/60

Abstract: A computer-implemented method is provided. The computer-implemented method includes rendering a dynamic effect to one or more objects in an image. The method includes setting boundary points surrounding a foreground object to define a boundary area in which a dynamic movement is to be realized; setting a movement line to define a dynamic movement direction along which the dynamic movement is to be realized, wherein setting the movement line includes detecting a continuous touch over different positions on the touch control display panel; setting a stationary area to define an area in which the dynamic movement is prohibited, wherein setting the stationary area includes detecting a first touch area corresponding to the stationary area on the touch control display panel; and generating an animation of the foreground object in the boundary area moving along the dynamic movement direction, thereby realizing the dynamic effect in the image.

公开(公告)号：US11908102B2

公开(公告)日：2024-02-20

申请号：US17281291

申请日：2020-05-28

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini ,  Dan Zhu ,  Lijie Zhang

IPC: G06N3/045 ,  G06N3/08

CPC classification number: G06T3/4046 ,  G06N3/045 ,  G06N3/08

Abstract: Disclosed are an image processing method and device, a training method of a neural network and a storage medium. The image processing method includes: obtaining an input image, and processing the input image by using a generative network to generate an output image. The generate network includes a first sub-network and at least one second sub-network, and the processing the input image by using the generative network to generate the output image includes, processing the input image by using the first sub-network to obtain a plurality of first feature images; performing a branching process and a weight sharing process on the plurality of first feature images by using the at least one second sub-network to obtain a plurality of second feature images; and processing the plurality of second feature images to obtain the output image.

公开(公告)号：US11705079B2

公开(公告)日：2023-07-18

申请号：US17532470

申请日：2021-11-22

Applicant: BOE Technology Group Co., Ltd.

Inventor： Yanhong Wu ,  Hanwen Liu ,  Lijie Zhang

IPC: G09G3/34

CPC classification number: G09G3/344 ,  G09G2320/0666 ,  G09G2340/06

Abstract: The present application discloses a color image processing method, a color image processing device, an electronic ink screen, and a storage medium. The color image processing method includes: obtaining an original image, and transforming original color data of a pixel in the original image into corresponding set color data in a set color space; determining a target color corresponding to the pixel in a plurality of set colors according to the set color data corresponding to the pixel and a color ratio allocation table; and generating a target image according to the target color.

公开(公告)号：US11620496B2

公开(公告)日：2023-04-04

申请号：US16069376

申请日：2017-11-17

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Pablo Navarrete Michelini ,  Hanwen Liu

IPC: G06N3/00 ,  G06N3/04

Abstract: A convolutional neural network, and a processing method, a processing device, a processing system and a medium for the same. The method includes: using an activation recorder layer as an activation function layer in the convolutional neural network, wherein in response to that a probe image with contents is inputted to the convolutional neural network, the activation recorder layer performs an activation operation the same as the activation function layer does and records an activation result of the activation operation; modifying the convolutional neural network, wherein step of modifying includes replacing the activation recorder layer with a hidden layer that uses the recorded activation result; and inputting an analysis image to the modified convolutional neural network as an input image, so as to output an output image of the modified convolutional neural network, thereby analyzing a forward effect or a backward effect between the input image and the output image, the analysis image being a pixel-level binary image.

公开(公告)号：US11216913B2

公开(公告)日：2022-01-04

申请号：US16855063

申请日：2020-04-22

Applicant: BOE Technology Group Co., Ltd.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini ,  Dan Zhu ,  Lijie Zhang

IPC: G06T5/00 ,  G06T3/40 ,  G06T5/20 ,  G06N3/08

Abstract: The present disclosure discloses a convolutional neural network processor, an image processing method and an electronic device. The method includes: receiving, by the first convolutional unit, the input image to be processed, extracting the N feature maps with different scales in the image to be processed, sending the N feature maps to the second convolutional unit, and sending the first feature map to the processing unit; fusing, by the processing unit, the received preset noise information and the first feature map, to obtain the second feature map, and sending the second feature map to the second convolutional unit; and fusing, by the second convolutional unit, the received N feature maps with the second feature map to obtain the processed image.

公开(公告)号：US11216910B2

公开(公告)日：2022-01-04

申请号：US16073712

申请日：2017-12-19

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini

IPC: G06T3/40 ,  G06N3/04 ,  G06N3/08 ,  G06T5/50

Abstract: An image processing system, an image processing method and a display device are provided. The image processing system includes at least one resolution conversion sub-system. The resolution conversion sub-system includes a CNN module, a combiner and an activation module connected in a cascaded manner. The CNN module is configured to perform convolution operation on an input signal to acquire a plurality of first feature images having a first resolution. The combiner is configured to combine the first feature images into a second feature image having a second resolution greater than the first resolution. The activation module is connected to the combiner and configured to perform a selection operation on the second feature image using an activation function.

公开(公告)号：US11138466B2

公开(公告)日：2021-10-05

申请号：US16338830

申请日：2018-08-20

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: An image processing method includes: obtaining an input image; performing image conversion processing on the input image by using a generative neural network; and outputting an output image that has been subjected to image conversion processing. The input image has N channels, N being a positive integer greater than or equal to 1; input of the generative neural network includes a noise image channel and N channels of the input image; output of the generative neural network is an output image including N channels.

公开(公告)号：US20210233214A1

公开(公告)日：2021-07-29

申请号：US16755044

申请日：2019-08-19

Applicant: BOE Technology Group Co., Ltd.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini ,  Dan Zhu ,  Lijie Zhang

IPC: G06T5/00 ,  G06N3/08

Abstract: A neural network is provided. The neural network includes 2n number of sampling units sequentially connected; and a plurality of processing units. A respective one of the plurality of processing units is between two adjacent sampling units of the 2n number of sampling units. A first sampling unit to an n-th sample unit of the 2n number of sampling units are DeMux units. A respective one of the DeMux units is configured to rearrange pixels in a respective input image to the respective one of the DeMux units following a first scrambling rule to obtain a respective rearranged image. An (n+1)-th sample unit to a (2n)-th sample unit of the 2n number of sampling units are Mux units. A respective one of the Mux units is configured to combine respective m′ number of input images to the respective one of the Mux units to obtain a respective combined image.

公开(公告)号：US20180211371A1

公开(公告)日：2018-07-26

申请号：US15717225

申请日：2017-09-27

Applicant: BOE Technology Group Co., Ltd.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini

IPC: G06T5/40 ,  H04N5/21 ,  H04N9/64

CPC classification number: G06T5/40 ,  G06T5/50 ,  G06T2207/10016 ,  G06T2207/20182 ,  H04N5/21 ,  H04N9/646

Abstract: The disclosure discloses an apparatus and method for correcting a flicker in a video, and a video device, the method including: determining a correction weight for correcting grayscale values of a current frame of video image according to a ratio of a variance of a histogram of mapped grayscale values of a last frame of video image to a variance of a histogram of grayscale values of the last frame of video image, and a contrast enhancement upper limit parameter input by a user, and/or a largest percentage of the number of pixels with a same grayscale among a total number of pixels in the histogram of the grayscale values of the last frame of video image, and the contrast enhancement upper limit parameter input by the user; and, determining resulting grayscale values of the current frame of video image according to the correction weight.

公开(公告)号：US12164560B2

公开(公告)日：2024-12-10

申请号：US17255458

申请日：2019-11-28

Applicant: BOE Technology Group Co., Ltd.

Inventor： Hanwen Liu ,  Pablo Navarrete Michelini ,  Dan Zhu

IPC: G06F3/04842 ,  G06F3/04847 ,  G06F16/55 ,  G06F16/58 ,  G06V10/20

Abstract: The present disclosure discloses a user interface system, electronic equipment and an interaction method for picture recognition. The electronic equipment includes a display screen, a memory and a processor, a first interface is displayed on the display screen, and the first interface includes at least one primary function classification tag, a plurality of secondary function classification tags and at least one tertiary function classification tag included in each of the secondary function classification tags; and by selecting a tertiary function classification tag, a second interface can be displayed such that a function effect corresponding to the tertiary function classification tag is experienced on the second interface. The electronic equipment can be used such that different tertiary function classification tags can be selected for experience in the first interface, can provide users with practicality, and has certain tool properties.