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公开(公告)号：US11272114B2
公开(公告)日：2022-03-08
申请号：US16875407
申请日：2020-05-15
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Dokwan Oh
Abstract: A method of obtaining an image from an image sensor provided in a vehicle includes obtaining a vehicle speed of the vehicle; adjusting a shutter speed of the image sensor; adjusting either one or both of an international organization for standardization sensitivity (ISO) of the image sensor and an aperture of the image sensor based on the vehicle speed; and obtaining the image from the image sensor based on the adjusted shutter speed and the adjusted either one or both of the ISO and the aperture.
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2.发明授权公开(公告)号：US12039016B2
公开(公告)日：2024-07-16
申请号：US15933609
申请日：2018-03-23
Applicant: Samsung Electronics Co., Ltd.
Inventor： Dokwan Oh , Yoonsuk Hyun
IPC: G06F21/31 , G06F18/21 , G06F18/214 , G06F18/2415 , G06N3/045 , G06N3/08 , G06N7/01 , G06V10/764 , G06V10/778 , G06V20/00
CPC classification number: G06F21/31 , G06F18/2148 , G06F18/2178 , G06F18/2415 , G06N3/045 , G06N3/08 , G06N7/01 , G06V10/764 , G06V10/7784 , G06V20/00
Abstract: Disclosed is a training data generating apparatus and method to change output data inappropriate for training a student model to an ignore value such that the inappropriate output data is not used to train the student model, change output data appropriate for training the student model such that the student model outputs an improved result in comparison to output data of a teacher model, and change a label value in a form of probability to an identifier corresponding to intervals divided based on threshold label values using the teacher model based on input data.
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公开(公告)号：US10708510B2
公开(公告)日：2020-07-07
申请号：US15805741
申请日：2017-11-07
Applicant: Samsung Electronics Co., Ltd.
Inventor： Dokwan Oh
Abstract: A method of obtaining an image from an image sensor provided in a vehicle includes obtaining a vehicle speed of the vehicle; adjusting a shutter speed of the image sensor; adjusting either one or both of an international organization for standardization sensitivity (ISO) of the image sensor and an aperture of the image sensor based on the vehicle speed; and obtaining the image from the image sensor based on the adjusted shutter speed and the adjusted either one or both of the ISO and the aperture.
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公开(公告)号：US12229965B2
公开(公告)日：2025-02-18
申请号：US17578639
申请日：2022-01-19
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Suji Kim , Seungjun Shin , Dokwan Oh
IPC: G06T7/11 , B60K35/28 , B60K37/00 , B60W10/04 , B60W10/20 , G06V10/764 , G06V10/771 , G06V10/774 , G06V10/82 , G06V20/58
Abstract: An electronic device extracts feature data from an input image, calculates one or more class maps from the feature data using a classifier layer, calculates one or more cluster maps from the feature data using a clustering layer, and generates image segmentation data using the one or more class maps and the one or more cluster maps.
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公开(公告)号：US12169917B2
公开(公告)日：2024-12-17
申请号：US17575002
申请日：2022-01-13
Applicant: Samsung Electronics Co., Ltd.
Inventor： Sujin Jang , Joohan Na , Dokwan Oh
Abstract: A processor-implemented method with data processing using a neural network includes: determining a first translated image by translating a first image based on a second image, the first image and a second image that having different distortions, such that a distortion of the first image corresponds to a distortion of the second image; determining a first retranslated image by translating the first translated image such that a distortion of the first translated image corresponds to a distortion of the first image; and training a first deformation field generator configured to determine a first relative deformation field that represents a relative deformation from the first image to the second image and a second deformation field generator configured to determine a second relative deformation field that represents a relative deformation from the second image to the first image, based on a loss between the first retranslated image and the first image.
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Patent Agency Ranking
公开(公告)号：US11636698B2
公开(公告)日：2023-04-25
申请号：US17368917
申请日：2021-07-07
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Cheolhun Jang , Dokwan Oh , Dae Hyun Ji
Abstract: A method and apparatus for adjusting a neural network that classifies a scene of an input image into at least one class is provided. The method generates a feature image having a size that is less than a size of an input image by applying a convolutional network to the input image, determines at least one class corresponding to the feature image, generates a class image having a size corresponding to the size of the input image by applying a deconvolutional network to the feature image, calculates a loss of the class image based on a verification class image preset with respect to the input image, and adjusts the neural network based on the loss.
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公开(公告)号：US12272158B2
公开(公告)日：2025-04-08
申请号：US17862821
申请日：2022-07-12
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Nayeon Kim , Moonsub Byeon , Dokwan Oh , Dae Hyun Ji
Abstract: A method of generating lane information using a neural network includes generating a lane probability map based on an input image, generating lane feature information and depth feature information by applying the lane probability map to a second neural network, generating depth distribution information by applying the depth feature information to a third neural network, generating spatial information based on the lane feature information and the depth distribution information, generating offset information including a displacement between a position of a lane and a reference line by applying the spatial information to a fourth neural network, and generating three-dimensional (3D) lane information using the offset information.
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8.发明申请公开(公告)号：US20250056024A1
公开(公告)日：2025-02-13
申请号：US18733379
申请日：2024-06-04
Applicant: SAMSUNG ELECTRONICS CO., LTD. , UNIVERSITY-INDUSTRY COOPERATION GROUP OF KYUNG HEE UNIVERSITY
Inventor： Seung Eon KIM , Yeongwoong Kim , Hui Yong Kim , Won Hee Lee , Suyong Bahk , Young Hun Sung , Dokwan Oh
IPC: H04N19/42 , H04N19/105 , H04N19/124 , H04N19/13 , H04N19/139 , H04N19/31 , H04N19/61 , H04N19/80 , H04N19/85
Abstract: There is provided a method for neural network-based video encoding. The method includes estimating a motion vector between an input image and a reference image based on a temporal layer of the input image, transforming the motion vector into a latent representation, scaling the latent representation of the motion vector based on the temporal layer of the input image and obtaining a temporal context of the input image based on the scaled latent representation of the motion vector and the reference image.
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公开(公告)号：US11240440B2
公开(公告)日：2022-02-01
申请号：US16875407
申请日：2020-05-15
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Dokwan Oh
Abstract: A method of obtaining an image from an image sensor provided in a vehicle includes obtaining a vehicle speed of the vehicle; adjusting a shutter speed of the image sensor; adjusting either one or both of an international organization for standardization sensitivity (ISO) of the image sensor and an aperture of the image sensor based on the vehicle speed; and obtaining the image from the image sensor based on the adjusted shutter speed and the adjusted either one or both of the ISO and the aperture.
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公开(公告)号：US11087185B2
公开(公告)日：2021-08-10
申请号：US16416898
申请日：2019-05-20
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Cheolhun Jang , Dokwan Oh , Dae Hyun Ji
Abstract: A method and apparatus for adjusting a neural network that classifies a scene of an input image into at least one class is provided. The method generates a feature image having a size that is less than a size of an input image by applying a convolutional network to the input image, determines at least one class corresponding to the feature image, generates a class image having a size corresponding to the size of the input image by applying a deconvolutional network to the feature image, calculates a loss of the class image based on a verification class image preset with respect to the input image, and adjusts the neural network based on the loss.
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