Patents by Inventor Yongsup Park
Yongsup Park has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11961207Abstract: Provided is an image processing apparatus including a memory storing one or more instructions and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is further configured to execute the one or more instructions to generate a second image by performing a deconvolution operation on a first image and a kernel comprising one or more weights, set values of the one or more weights based on the second image, and adjust the values of the one or more weights based on positions of the one or more weights in the kernel.Type: GrantFiled: September 11, 2019Date of Patent: April 16, 2024Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Iljun Ahn, Yongsup Park, Jaeyeon Park, Minsu Cheon, Tammy Lee
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Publication number: 20240078631Abstract: An image processing apparatus applies an image to a first learning network model to optimize the edges of the image, applies the image to a second learning network model to optimize the texture of the image, and applies a first weight to the first image and a second weight to the second image based on information on the edge areas and the texture areas of the image to acquire an output image.Type: ApplicationFiled: November 10, 2023Publication date: March 7, 2024Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Cheon LEE, Donghyun KIM, Yongsup PARK, Jaeyeon PARK, Iljun AHN, Hyunseung LEE, Taegyoung AHN, Youngsu MOON, Tammy LEE
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Patent number: 11921822Abstract: Provided are an image processing apparatus and an operation method of the image processing apparatus. The image processing apparatus includes a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory to, by using one or more convolution neural networks, extract target features by performing a convolution operation between features of target regions having same locations in a plurality of input images and a first kernel set, extract peripheral features by performing a convolution operation of features of peripheral regions located around the target regions in the plurality of input images and a second kernel set, and determine a feature of a region corresponding to the target regions in an output image, based on the target features and the peripheral features.Type: GrantFiled: October 16, 2019Date of Patent: March 5, 2024Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jaeyeon Park, Iljun Ahn, Yongsup Park, Jaehee Kwak, Tammy Lee, Minsu Cheon
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Patent number: 11871144Abstract: Provided is an image processing apparatus for generating a high-resolution image. The image processing apparatus includes a memory storing one or more instructions and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is configured to extract feature information regarding a low-resolution image of a current frame by using a first convolutional neural network, generate, based on the feature information, a first high-resolution image of the current frame, remove flickering of the first high-resolution image by using a high-resolution image of a previous frame, and remove flickering of a high-resolution image of a next frame by using at least one of a flickering-removed second high-resolution image of the current frame, or the feature information.Type: GrantFiled: July 16, 2019Date of Patent: January 9, 2024Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Iljun Ahn, Yongsup Park, Jaeyeon Park, Tammy Lee, Minsu Cheon
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Patent number: 11861808Abstract: An electronic device is disclosed. The electronic device of the disclosure comprises: a memory in which a learned artificial intelligence model is stored; and a processor for inputting an input image to the artificial intelligence model and outputting an enlarged image with increased resolution, wherein the learned artificial intelligence model includes an upscaling module for acquiring the pixel values of interpolated pixels around a cell according to a function having a nonlinearly decreasing symmetric form with reference to an original pixel in the enlarged image, the original pixel corresponding to a pixel of the input image.Type: GrantFiled: February 20, 2019Date of Patent: January 2, 2024Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jaeyeon Park, Iljun Ahn, Yongsup Park, Tammy Lee, Minsu Cheon
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Patent number: 11836890Abstract: An image processing apparatus applies an image to a first learning network model to optimize the edges of the image, applies the image to a second learning network model to optimize the texture of the image, and applies a first weight to the first image and a second weight to the second image based on information on the edge areas and the texture areas of the image to acquire an output image.Type: GrantFiled: November 16, 2021Date of Patent: December 5, 2023Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Cheon Lee, Donghyun Kim, Yongsup Park, Jaeyeon Park, Iljun Ahn, Hyunseung Lee, Taegyoung Ahn, Youngsu Moon, Tammy Lee
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Patent number: 11825234Abstract: Provided is an image processing apparatus for generating a high-resolution image. The image processing apparatus includes a memory storing one or more instructions and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is configured to extract feature information regarding a low-resolution image of a current frame by using a first convolutional neural network, generate, based on the feature information, a first high-resolution image of the current frame, remove flickering of the first high-resolution image by using a high-resolution image of a previous frame, and remove flickering of a high-resolution image of a next frame by using at least one of a flickering-removed second high-resolution image of the current frame, or the feature information.Type: GrantFiled: July 16, 2019Date of Patent: November 21, 2023Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Iljun Ahn, Yongsup Park, Jaeyeon Park, Tammy Lee, Minsu Cheon
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Patent number: 11720998Abstract: An artificial intelligence (AI) decoding apparatus obtains image data corresponding to a first image, which is AI-downscaled from an original image by an AI encoding apparatus by using a first deep neural network (DNN); reconstructs a second image corresponding to the first image, based on the image data; and obtain a third image, which is AI-upscaled from the second image, convolution is performed based on the second image and second parameters of a filter kernel included in a second DNN, wherein each of the second parameters is an integer value, and the second parameters are determined as values associated with first parameters of a filter kernel included in the first DNN. Embodiments use memory-efficient values with respect to filter kernels. Parameters used to obtain the memory-efficient integer values may be obtained via joint training between the first DNN and the second DNN.Type: GrantFiled: November 6, 2020Date of Patent: August 8, 2023Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Quockhanh Dinh, Kwangpyo Choi, Yongsup Park, Jaeyeon Park
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Patent number: 11694306Abstract: An image processing apparatus for performing image quality processing on an image includes a feature extraction network and an image quality processing network including one or more modulation blocks, wherein each of the one or more modulation blocks includes a convolution layer, a modulation layer, and an activation layer for processing the image.Type: GrantFiled: April 26, 2021Date of Patent: July 4, 2023Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Sangwook Baek, Yongsup Park, Sangmi Lee, Youngo Park, Kwangpyo Choi
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Patent number: 11636626Abstract: An image providing apparatus configured to generate, by using a first artificial intelligence (AI) network, AI metadata including class information and at least one class map, in which the class information includes at least one class corresponding to a type of an object among a plurality of predefined objects included in a first image and the at least one class map indicates a region corresponding to each class in the first image, generate an encoded image by encoding the first image, and output the encoded image and the AI metadata through the output interface.Type: GrantFiled: November 20, 2020Date of Patent: April 25, 2023Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Sangwook Baek, Minsu Cheon, Yongsup Park, Jaeyeon Park, Kwangpyo Choi
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Patent number: 11380081Abstract: Provided is an image processing apparatus including a memory storing at least one instruction, and a processor configured to execute the at least one instruction stored in the memory to obtain first feature information by performing a convolution operation on a first image and a first kernel included in a first convolution layer among a plurality of convolution layers, obtain at least one piece of characteristic information, based on the first feature information; obtain second feature information, based on the first feature information and the at least one piece of characteristic information, obtain third feature information by performing a convolution operation on the obtained second feature information and a second kernel included in a second convolution layer that is a layer next to the first convolution layer among the plurality of convolution layers, and obtain an output image, based on the third feature information.Type: GrantFiled: April 29, 2020Date of Patent: July 5, 2022Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jaeyeon Park, Yongsup Park, Iljun Ahn, Sangwook Baek, Minsu Cheon, Kwangpyo Choi
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Patent number: 11315223Abstract: An image processing apparatus is disclosed. The present image processing apparatus comprises: a memory for storing a low dynamic range (LDR) image and a processor for adjusting the brightness of the LDR image by means of a pixel-specific brightness ratio identified using a first parameter, and acquiring a high dynamic range (HDR) image by adding or subtracting a pixel-specific correction value identified using a second parameter in the brightness-adjusted LDR image.Type: GrantFiled: January 24, 2019Date of Patent: April 26, 2022Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Minsu Cheon, Yongsup Park, Changhan Kim, Jaeyeon Park, Iljun Ahn, Heeseok Oh, Tammy Lee, Kiheum Cho
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Patent number: 11295412Abstract: An image processing apparatus applies an image to a first learning network model to optimize the edges of the image, applies the image to a second learning network model to optimize the texture of the image, and applies a first weight to the first image and a second weight to the second image based on information on the edge areas and the texture areas of the image to acquire an output image.Type: GrantFiled: April 2, 2020Date of Patent: April 5, 2022Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Cheon Lee, Donghyun Kim, Yongsup Park, Jaeyeon Park, Iljun Ahn, Hyunseung Lee, Taegyoung Ahn, Youngsu Moon, Tammy Lee
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Publication number: 20220076375Abstract: An image processing apparatus applies an image to a first learning network model to optimize the edges of the image, applies the image to a second learning network model to optimize the texture of the image, and applies a first weight to the first image and a second weight to the second image based on information on the edge areas and the texture areas of the image to acquire an output image.Type: ApplicationFiled: November 16, 2021Publication date: March 10, 2022Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Cheon LEE, Donghyun KIM, Yongsup PARK, Jaeyeon PARK, lljun AHN, Hyunseung LEE, Taegyoung AHN, Youngsu MOON, Tammy LEE
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Publication number: 20220019844Abstract: An image processing apparatus includes a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory. The processor is configured to, by using one or more convolution neural networks, extract target features by performing a convolution operation between features of target regions having same locations in a plurality of input images and a first kernel set, extract peripheral features by performing a convolution operation of features of peripheral regions located around the target regions in the plurality of input images and a second kernel set, and determine a feature of a region corresponding to the target regions in an output image, based on the target features and the peripheral features.Type: ApplicationFiled: October 16, 2019Publication date: January 20, 2022Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jaeyeon PARK, Iljun AHN, Yongsup PARK, Jaehee KWAK, Tammy LEE, Minsu CHEON
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Publication number: 20210390660Abstract: An image processing apparatus for performing image quality processing on an image includes a feature extraction network and an image quality processing network including one or more modulation blocks, wherein each of the one or more modulation blocks includes a convolution layer, a modulation layer, and an activation layer for processing the image.Type: ApplicationFiled: April 26, 2021Publication date: December 16, 2021Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Sangwook BAEK, Yongsup PARK, Sangmi LEE, Youngo PARK, Kwangpyo CHOI
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Publication number: 20210224951Abstract: Provided is an image processing apparatus for generating a high-resolution image. The image processing apparatus includes a memory storing one or more instructions and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is configured to extract feature information regarding a low-resolution image of a current frame by using a first convolutional neural network, generate, based on the feature information, a first high-resolution image of the current frame, remove flickering of the first high-resolution image by using a high-resolution image of a previous frame, and remove flickering of a high-resolution image of a next frame by using at least one of a flickering-removed second high-resolution image of the current frame, or the feature information.Type: ApplicationFiled: July 16, 2019Publication date: July 22, 2021Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Iljun AHN, Yongsup PARK, Jaeyeon PARK, Tammy LEE, Minsu CHEON
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Publication number: 20210183015Abstract: Provided is an image processing apparatus including a memory storing one or more instructions and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is further configured to execute the one or more instructions to generate a second image by performing a deconvolution operation on a first image and a kernel comprising one or more weights, set values of the one or more weights based on the second image, and adjust the values of the one or more weights based on positions of the one or more weights in the kernel.Type: ApplicationFiled: September 11, 2019Publication date: June 17, 2021Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Iljun AHN, Yongsup PARK, Jaeyeon PARK, Minsu CHEON, Tammy LEE
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Publication number: 20210150287Abstract: An image providing apparatus configured to generate, by using a first artificial intelligence (AI) network, AI metadata including class information and at least one class map, in which the class information includes at least one class corresponding to a type of an object among a plurality of predefined objects included in a first image and the at least one class map indicates a region corresponding to each class in the first image, generate an encoded image by encoding the first image, and output the encoded image and the AI metadata through the output interface.Type: ApplicationFiled: November 20, 2020Publication date: May 20, 2021Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Sangwook BAEK, Minsu CHEON, Yongsup PARK, Jaeyeon PARK, Kwangpyo CHOI
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Publication number: 20210142445Abstract: An artificial intelligence (AI) decoding apparatus obtains image data corresponding to a first image, which is AI-downscaled from an original image by an AI encoding apparatus by using a first deep neural network (DNN); reconstructs a second image corresponding to the first image, based on the image data; and obtain a third image, which is AI-upscaled from the second image, convolution is performed based on the second image and second parameters of a filter kernel included in a second DNN, wherein each of the second parameters is an integer value, and the second parameters are determined as values associated with first parameters of a filter kernel included in the first DNN. Embodiments use memory-efficient values with respect to filter kernels. Parameters used to obtain the memory-efficient integer values may be obtained via joint training between the first DNN and the second DNN.Type: ApplicationFiled: November 6, 2020Publication date: May 13, 2021Applicant: SAMSUNG ELECTRONICS CO,. LTD.Inventors: Quockhanh DINH, Kwangpyo CHOI, Yongsup PARK, Jaeyeon PARK