Patents by Inventor Sun-Young Jeon
Sun-Young Jeon 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: 11974469Abstract: Disclosed is a display device and a method of manufacturing the same having improved reliability. In the display device, at least one of a plurality of dielectric films disposed between an oxide semiconductor layer and a light-emitting device includes a lower region disposed on the oxide semiconductor layer and an upper region disposed on the lower region, the upper region including a trap element configured to trap hydrogen, whereby reliability of a thin film transistor including the oxide semiconductor layer is improved.Type: GrantFiled: August 25, 2021Date of Patent: April 30, 2024Assignee: LG Display Co., Ltd.Inventors: Jae Hyun Kim, Jin Chae Jeon, Sun Young Choi, Mi Jin Jeong, Jeoung In Lee
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Patent number: 11218695Abstract: Provided is in-loop filtering technology using a trained deep neural network (DNN) filter model. An image decoding method according to an embodiment includes receiving a bitstream of an encoded image, generating reconstructed data by reconstructing the encoded image, obtaining information about a content type of the encoded image from the bitstream, determining a deep neural network (DNN) filter model trained to perform in-loop filtering by using at least one computer, based on the information about the content type, and performing the in-loop filtering by applying the reconstructed data to the determined DNN filter model.Type: GrantFiled: February 6, 2018Date of Patent: January 4, 2022Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Young-o Park, Jae-hwan Kim, Jong-seok Lee, Sun-young Jeon, Jeong-hoon Park, Kwang-pyo Choi
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Patent number: 11197013Abstract: Provided is a prediction image generating technology using a deep neural network (DNN). Provided is an image decoding method including: receiving a bitstream of an encoded image; determining at least one block split from the encoded image; determining neighboring blocks for predicting a current block among the at least one block; generating prediction data of the current block by applying the neighboring blocks to a DNN learning model configured to predict a block of an image by using at least one computer; extracting residual data of the current block from the bitstream; and reconstructing the current block by using the prediction data and the residual data.Type: GrantFiled: February 6, 2018Date of Patent: December 7, 2021Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jong-seok Lee, Jae-hwan Kim, Young-o Park, Jeong-hoon Park, Sun-young Jeon, Kwang-pyo Choi
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Patent number: 11190784Abstract: Provided are an image compressing method including determining a compressed image by performing downsampling using a deep neural network (DNN) on an image; determining a prediction signal by performing prediction based on the compressed image; determining a residual signal based on the compressed image and the prediction signal; and generating a bitstream comprising information about the residual signal, wherein the DNN has a network structure that is predetermined according to training of a downsampling process using information generated in an upsampling process, and an image compressing device for performing the image compressing method. Also, provided are an image reconstructing method of reconstructing a compressed image by using a DNN for upsampling, the compressed image having been compressed by the image compressing method, and an image reconstructing device for performing the image reconstructing method.Type: GrantFiled: February 6, 2018Date of Patent: November 30, 2021Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jae-hwan Kim, Young-o Park, Jeong-hoon Park, Jong-seok Lee, Sun-young Jeon, Kwang-pyo Choi
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Patent number: 11095894Abstract: Provided is a method of encoding an image, the method including: determining a subjective quality of the image when the image is compressed; determining at least one degree of compression that changes the subjective quality and is from among degrees of compression indicating how much the image is compressed; and encoding the image by compressing a residual signal of the image, based on compression information according to the determined degree of compression, wherein the subjective quality is determined for each frame by using a Deep Neural Network (DNN). Provided are an image decoding method and an image decoding apparatus for performing the image decoding method for decoding an image by using information encoded according to an image encoding method.Type: GrantFiled: February 6, 2018Date of Patent: August 17, 2021Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Sun-young Jeon, Jae-hwan Kim, Young-o Park, Jeong-hoon Park, Jong-seok Lee, Kwang-pyo Choi
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Publication number: 20210160522Abstract: Provided is a prediction image generating technology using a deep neural network (DNN). Provided is an image decoding method including: receiving a bitstream of an encoded image; determining at least one block split from the encoded image; determining neighboring blocks for predicting a current block among the at least one block; generating prediction data of the current block by applying the neighboring blocks to a DNN learning model configured to predict a block of an image by using at least one computer; extracting residual data of the current block from the bitstream; and reconstructing the current block by using the prediction data and the residual data.Type: ApplicationFiled: February 6, 2018Publication date: May 27, 2021Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jong-seok LEE, Jae-hwan KIM, Young-o PARK, Jeong-hoon PARK, Sun-young JEON, Kwang-pyo CHOI
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Patent number: 10986356Abstract: Provided are an image compressing method including determining a compressed image by performing downsampling using a deep neural network (DNN) on an image; determining a prediction signal by performing prediction based on the compressed image; determining a residual signal based on the compressed image and the prediction signal; and generating a bitstream comprising information about the residual signal, wherein the DNN has a network structure that is predetermined according to training of a downsampling process using information generated in an upsampling process, and an image compressing device for performing the image compressing method. Also, provided are an image reconstructing method of reconstructing a compressed image by using a DNN for upsampling, the compressed image having been compressed by the image compressing method, and an image reconstructing device for performing the image reconstructing method.Type: GrantFiled: January 23, 2020Date of Patent: April 20, 2021Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jae-hwan Kim, Young-o Park, Jeong-hoon Park, Jong-seok Lee, Sun-young Jeon, Kwang-pyo Choi
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Publication number: 20200389658Abstract: Provided are an image compressing method including determining a compressed image by performing downsampling using a deep neural network (DNN) on an image; determining a prediction signal by performing prediction based on the compressed image; determining a residual signal based on the compressed image and the prediction signal; and generating a bitstream comprising information about the residual signal, wherein the DNN has a network structure that is predetermined according to training of a downsampling process using information generated in an upsampling process, and an image compressing device for performing the image compressing method. Also, provided are an image reconstructing method of reconstructing a compressed image by using a DNN for upsampling, the compressed image having been compressed by the image compressing method, and an image reconstructing device for performing the image reconstructing method.Type: ApplicationFiled: February 6, 2018Publication date: December 10, 2020Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jae-hwan KIM, Young-o PARK, Jeong-hoon PARK, Jong-seok LEE, Sun-young JEON, Kwang-pyo CHOI
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Patent number: 10796419Abstract: An electronic apparatus includes a memory configured to store a predetermined conversion relation, and a processor configured to obtain first luminance information indicating luminance values of respective pixels included in a first image, and obtain first color information indicating color values of the respective pixels, obtain a first cumulative distribution function indicating a relation between a cumulative pixel count and each luminance level based on the first luminance information, obtain a second cumulative distribution function by applying the predetermined conversion relation to the first cumulative distribution function, calculate second luminance information indicating converted luminance values of the respective pixels by using the first cumulative distribution function and the second cumulative distribution function, and generate a second image based on the first color information and the second luminance information.Type: GrantFiled: June 7, 2018Date of Patent: October 6, 2020Assignees: SAMSUNG ELECTRONICS CO., LTD., INDUSTRY-ACADEMIC COOPERATION FOUNDATION, YONSEI UNIVERSITYInventors: Dosik Hwang, Kihun Bang, Hanbyol Jang, Jinseong Jang, Min-su Cheon, Young-o Park, Sun-young Jeon
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Publication number: 20200162751Abstract: Provided are an image compressing method including determining a compressed image by performing downsampling using a deep neural network (DNN) on an image; determining a prediction signal by performing prediction based on the compressed image; determining a residual signal based on the compressed image and the prediction signal; and generating a bitstream comprising information about the residual signal, wherein the DNN has a network structure that is predetermined according to training of a downsampling process using information generated in an upsampling process, and an image compressing device for performing the image compressing method. Also, provided are an image reconstructing method of reconstructing a compressed image by using a DNN for upsampling, the compressed image having been compressed by the image compressing method, and an image reconstructing device for performing the image reconstructing method.Type: ApplicationFiled: January 23, 2020Publication date: May 21, 2020Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jae-hwan KIM, Young-o PARK, Jeong-hoon PARK, Jong-seok LEE, Sun-young JEON, Kwang-pyo CHOI
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Publication number: 20200145661Abstract: Provided is a method of encoding an image, the method including: determining a subjective quality of the image when the image is compressed; determining at least one degree of compression that changes the subjective quality and is from among degrees of compression indicating how much the image is compressed; and encoding the image by compressing a residual signal of the image, based on compression information according to the determined degree of compression, wherein the subjective quality is determined for each frame by using a Deep Neural Network (DNN). Provided are an image decoding method and an image decoding apparatus for performing the image decoding method for decoding an image by using information encoded according to an image encoding method.Type: ApplicationFiled: February 6, 2018Publication date: May 7, 2020Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Sun-young JEON, Jae-hwan KIM, Young-o PARK, Jeong-hoon PARK, Jong-seok LEE, Kwang-pyo CHOI
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Publication number: 20200120340Abstract: Provided is in-loop filtering technology using a trained deep neural network (DNN) filter model. An image decoding method according to an embodiment includes receiving a bitstream of an encoded image, generating reconstructed data by reconstructing the encoded image, obtaining information about a content type of the encoded image from the bitstream, determining a deep neural network (DNN) filter model trained to perform in-loop filtering by using at least one computer, based on the information about the content type, and performing the in-loop filtering by applying the reconstructed data to the determined DNN filter model.Type: ApplicationFiled: February 6, 2018Publication date: April 16, 2020Applicant: SAMSUNG ELECTRONICS CO., LTD.Inventors: Young-o PARK, Jae-hwan KIM, Jong-seok LEE, Sun-young JEON, Jeong-hoon PARK, Kwang-pyo CHOI
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Publication number: 20190228510Abstract: An electronic apparatus includes a memory configured to store a predetermined conversion relation, and a processor configured to obtain first luminance information indicating luminance values of respective pixels included in a first image, and obtain first color information indicating color values of the respective pixels, obtain a first cumulative distribution function indicating a relation between a cumulative pixel count and each luminance level based on the first luminance information, obtain a second cumulative distribution function by applying the predetermined conversion relation to the first cumulative distribution function, calculate second luminance information indicating converted luminance values of the respective pixels by using the first cumulative distribution function and the second cumulative distribution function, and generate a second image based on the first color information and the second luminance information.Type: ApplicationFiled: June 7, 2018Publication date: July 25, 2019Applicants: SAMSUNG ELECTRONICS CO., LTD., INDUSTRY-ACADEMIC COOPERATION FOUNDATION, YONSEI U NIVERSITYInventors: Dosik HWANG, Kihun BANG, Hanbyol JANG, Jinseong JANG, Min-su CHEON, Young-o PARK, Sun-young JEON
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Patent number: 8135069Abstract: A Frame Rate Conversion (FRC) method using motion interpolation is disclosed. The FRC method includes checking the position of a motion vector intersecting an interpolated frame for each block of the interpolated frame, performing motion interpolation by acquiring a motion vector of each vertex of each block using motion vectors adjacent to each vertex, and performing motion interpolation on pixels of each block using the motion vector of each vertex.Type: GrantFiled: September 20, 2007Date of Patent: March 13, 2012Assignee: Samsung Electronics Co., Ltd.Inventors: Sun-Young Jeon, Young-Hun Joo, Yong-Hyun Lim, Bong-Gon Kim, Yun-Je Oh
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Publication number: 20080101472Abstract: A Frame Rate Conversion (FRC) method using motion interpolation is disclosed. The FRC method includes checking the position of a motion vector intersecting an interpolated frame for each block of the interpolated frame, performing motion interpolation by acquiring a motion vector of each vertex of each block using motion vectors adjacent to each vertex, and performing motion interpolation on pixels of each block using the motion vector of each vertex.Type: ApplicationFiled: September 20, 2007Publication date: May 1, 2008Inventors: Sun-Young Jeon, Young-Hun Joo, Yong-Hyun Lim, Bong-Gon Kim, Yun-Je Oh