-
31.发明授权Communication system with modulation classifier and method of operation thereof 有权具有调制分类器的通信系统及其操作方法公开(公告)号：US08953667B2
公开(公告)日：2015-02-10
申请号：US14155964
申请日：2014-01-15
Applicant: Samsung Electronics Co., Ltd.
Inventor： Dongwoon Bai , Jungwon Lee , Sungsoo Kim , Jung Hyun Bae , Jooyeol Yang , Inyup Kang
CPC classification number: H04L27/0012
Abstract: A method of operation of a communication system includes: calculating a shift distance of a received signal having a distortion; calculating an approximate likelihood of the received signal matching a transmitted signal from the shift distance; determining a bias factor from the distortion; and selecting a determined modulation maximizing a combination of the approximate likelihood and the bias factor for communicating with a device.
Abstract translation: 一种通信系统的操作方法包括：计算具有失真的接收信号的移位距离; 计算所述接收信号与所述移动距离匹配的发送信号的近似似然度; 从失真中确定偏差因子; 以及选择最大化用于与设备通信的近似似然性和偏差因子的组合的确定的调制。
-
公开(公告)号：US12079972B2
公开(公告)日：2024-09-03
申请号：US17572223
申请日：2022-01-10
Applicant: Samsung Electronics Co., Ltd.
Inventor： Seongjun Park , Shuangquan Wang , Dongwoon Bai , Jungwon Lee
Abstract: A method of performing scene-dependent lens shading correction (SD-LSC) is provided. The method includes collecting scene information from a Bayer thumbnail of an input image; generating a standard red green blue (sRGB) thumbnail by processing the Bayer thumbnail of the input image to simulate white balance (WB) and pre-gamma blocks; determining a representative color channel ratio of the input image based on the scene information and the sRGB thumbnail; determining an ideal grid gain of the input image based on the representative color channel ratio and a grid gain of the input image; merging the ideal grid gain and the grid gain of the input image to generate a new grid gain; and applying the new grid gain to the input image.
-
33.发明授权公开(公告)号：US11741577B2
公开(公告)日：2023-08-29
申请号：US17244504
申请日：2021-04-29
Applicant: Samsung Electronics Co., Ltd.
Inventor： Mojtaba Rahmati , Dongwoon Bai , Jungwon Lee
CPC classification number: G06T5/002 , G06T5/50 , G06T2207/20012
Abstract: A method and system are provided. The method includes determining a difference map between a reference frame and a non-reference frame, determining a local variance of the reference frame, determining a detail power map based on a difference between the determined local variance and the determined difference map, and determining a detail grade map based on the determined detail power map.
-
公开(公告)号：US20220414919A1
公开(公告)日：2022-12-29
申请号：US17726124
申请日：2022-04-21
Applicant: Samsung Electronics Co., Ltd.
Inventor： Abhishek TYAGI , Yangwen Liang , Shuangquan Wang , Dongwoon Bai , Vignesh Sethuraman , Xue Li
Abstract: A method and an apparatus are provided for performing visual inertial odometry (VIO). Measurements are processed from an inertial measurement unit (IMU), a camera, and a depth sensor. Keyframe residue including at least depth residue is determined based on the processed measurements. A sliding window graph is generated and optimized based on factors derived from the keyframe residue. An object pose is estimated based on the optimized sliding window graph.
-
公开(公告)号：US20220375044A1
公开(公告)日：2022-11-24
申请号：US17572223
申请日：2022-01-10
Applicant: Samsung Electronics Co., Ltd.
Inventor： Seongjun Park , Shuangquan Wang , Dongwoon Bai , Jungwon Lee
Abstract: A method of performing scene-dependent lens shading correction (SD-LSC) is provided. The method includes collecting scene information from a Bayer thumbnail of an input image; generating a standard red green blue (sRGB) thumbnail by processing the Bayer thumbnail of the input image to simulate white balance (WB) and pre-gamma blocks; determining a representative color channel ratio of the input image based on the scene information and the sRGB thumbnail; determining an ideal grid gain of the input image based on the representative color channel ratio and a grid gain of the input image; merging the ideal grid gain and the grid gain of the input image to generate a new grid gain; and applying the new grid gain to the input image.
-
Patent Agency Ranking
公开(公告)号：US11461998B2
公开(公告)日：2022-10-04
申请号：US16777734
申请日：2020-01-30
Applicant: Samsung Electronics Co., Ltd.
Inventor： Qingfeng Liu , Mostafa El-Khamy , Dongwoon Bai , Jungwon Lee
Abstract: Some aspects of embodiments of the present disclosure relate to using a boundary aware loss function to train a machine learning model for computing semantic segmentation maps from input images. Some aspects of embodiments of the present disclosure relate to deep convolutional neural networks (DCNNs) for computing semantic segmentation maps from input images, where the DCNNs include a box filtering layer configured to box filter input feature maps computed from the input images before supplying box filtered feature maps to an atrous spatial pyramidal pooling (ASPP) layer. Some aspects of embodiments of the present disclosure relate to a selective ASPP layer configured to weight the outputs of an ASPP layer in accordance with attention feature maps.
-
公开(公告)号：US11423510B2
公开(公告)日：2022-08-23
申请号：US16814184
申请日：2020-03-10
Applicant: Samsung Electronics Co., Ltd.
Inventor： Rohit R. Ranade , Yangwen Liang , Shuangquan Wang , Dongwoon Bai , Jungwon Lee
Abstract: A method and an apparatus are provided for providing a dolly zoom effect by an electronic device. A first image with a first depth map and a second image with a second depth map are obtained. A first synthesized image and a corresponding first synthesized depth map are generated using the first image and the first depth map respectively. A second synthesized image and a corresponding second synthesized depth map are generated using the second image and the second depth map respectively. A fused image is generated from the first synthesized image and the second synthesized image. A fused depth map is generated from the first synthesized depth map and the second synthesized depth map. A final synthesized image is generated based on processing the fused image and the fused depth map.
-
公开(公告)号：US20220122311A1
公开(公告)日：2022-04-21
申请号：US17166586
申请日：2021-02-03
Applicant: Samsung Electronics Co., Ltd.
Inventor： Rohit R. Ranade , Yangwen Liang , Shuangquan Wang , Dongwoon Bai , Jungwon Lee
Abstract: An electronic device and method for texturing a three dimensional (3D) model are provided. The method includes rendering a texture atlas to obtain a first set of two dimensional (2D) images of the 3D model; rendering a ground truth texture atlas to obtain a second set of 2D images of the 3D model; comparing the first set of images with the second set of images to determine a rendering loss; applying the texture sampling properties to a convolutional neural network (CNN) to incorporate the rendering loss into a deep learning framework; and inputting a 2D texture atlas into the CNN to generate a texture of the 3D module.
-
公开(公告)号：US20210174082A1
公开(公告)日：2021-06-10
申请号：US17177720
申请日：2021-02-17
Applicant: Samsung Electronics Co., Ltd.
Inventor： Qingfeng Liu , Mostafa El-Khamy , Rama Mythili Vadali , Tae-ui Kim , Andrea Kang , Dongwoon Bai , Jungwon Lee , Maiyuran Wijay , Jaewon Yoo
Abstract: A method for computing a dominant class of a scene includes: receiving an input image of a scene; generating a segmentation map of the input image, the segmentation map being labeled with a plurality of corresponding classes of a plurality of classes; computing a plurality of area ratios based on the segmentation map, each of the area ratios corresponding to a different class of the plurality of classes of the segmentation map; and outputting a detected dominant class of the scene based on a plurality of ranked labels based on the area ratios.
-
公开(公告)号：US20210089807A1
公开(公告)日：2021-03-25
申请号：US16777734
申请日：2020-01-30
Applicant: Samsung Electronics Co., Ltd.
Inventor： Qingfeng Liu , Mostafa El-Khamy , Dongwoon Bai , Jungwon Lee
Abstract: Some aspects of embodiments of the present disclosure relate to using a boundary aware loss function to train a machine learning model for computing semantic segmentation maps from input images. Some aspects of embodiments of the present disclosure relate to deep convolutional neural networks (DCNNs) for computing semantic segmentation maps from input images, where the DCNNs include a box filtering layer configured to box filter input feature maps computed from the input images before supplying box filtered feature maps to an atrous spatial pyramidal pooling (ASPP) layer. Some aspects of embodiments of the present disclosure relate to a selective ASPP layer configured to weight the outputs of an ASPP layer in accordance with attention feature maps.
-
-
-
-
-
-
-
-
-
Search Results
68
records
(took 0.023 seconds)
