公开(公告)号：US20240280893A1

公开(公告)日：2024-08-22

申请号：US18411594

申请日：2024-01-12

Applicant: KOREA ELECTRONICS TECHNOLOGY INSTITUTE

Inventor： Hyeong Keun KIM ,  Seul Gi KIM

IPC: G03F1/64

CPC classification number: G03F1/64

Abstract: Proposed is a pellicle for extreme ultraviolet (EUV) lithography based on a nanotube and having good optical properties, thermal stability, mechanical stability and chemical durability. The pellicle may include a frame having an opening formed in a central portion, and a pellicle membrane supported by the frame and covering the opening. The pellicle membrane may be formed in a reticular structure based on nanotubes, and include a coating layer formed by coating at least part of the nanotubes with a metal or metal compound. The metal or metal compound may be based on at least one of Mo, Si, Zr, Nb, Ru, Y, La, or Ce, or any alloy thereof.

公开(公告)号：US12067435B2

公开(公告)日：2024-08-20

申请号：US17623221

申请日：2021-12-07

Applicant: Korea Electronics Technology Institute

Inventor： Sung Hee Hong ,  Young Min Kim ,  Ji Soo Hong

IPC: G06K19/06 ,  G06K19/16

CPC classification number: G06K19/06037 ,  G06K19/16 ,  G06K2207/1015

Abstract: Provided is an uncopyable hologram QR code, According to an embodiment of the present disclosure, a 3D code generation method divides a 2D code having specific information recorded thereon into a plurality of sub 2D codes, and generatES a 3D code by coupling at least one of the divided sub 2D codes at a different depth. Accordingly, a QR code is recorded on a hologram recording medium as a hologram, and is displayed and scanned, so that it is impossible to easily duplicate the QR code unlike an existing 2D QR code.

公开(公告)号：US20240253124A1

公开(公告)日：2024-08-01

申请号：US18565816

申请日：2022-05-25

Applicant: Korea Electronics Technology Institute

Inventor： Jae Ho SHIN ,  Hwa Seon SHIN ,  Hye In LEE ,  Sung Hwan CHUN ,  Sung Hun PARK

IPC: B22F10/366 ,  B22F10/80 ,  B33Y50/02 ,  G01N25/72

CPC classification number: B22F10/366 ,  B22F10/80 ,  G01N25/72 ,  B33Y50/02

Abstract: A thermal-analysis-based output stabilization method and system for improving 3D printing output reliability are provided. The thermal-analysis-based output stabilization method according to an embodiment of the present invention comprises steps in which: an output stabilization system performs first stacking thermal analysis on a plurality of residual heat quantity review specimens for which a process range corresponding to normal output quality is set; the output stabilization system performs second stacking thermal analysis on an actual stacked product on the basis of the first stacking thermal analysis result in the same manner as the first stacking thermal analysis method; and the output stabilization system performs stability review on the stacking result of the stacked product on the basis of the second stacking thermal analysis result.

公开(公告)号：US20240249558A1

公开(公告)日：2024-07-25

申请号：US18289958

申请日：2022-06-20

Applicant: Korea Electronics Technology Institute

Inventor： Han Mu PARK ,  Jin Yea JANG ,  Sa Im SHIN

IPC: G06V40/20 ,  G06V10/774 ,  G06V20/40 ,  G06V40/16

CPC classification number: G06V40/28 ,  G06V10/774 ,  G06V20/46 ,  G06V20/49 ,  G06V40/175

Abstract: Provided are a method for segmenting sign language into morphemes, a method for predicting morpheme positions, and a method for augmenting data. A system for analyzing sign language according to an embodiment of the present invention comprises: a recognition unit which recognizes key points of a speaker from a sign language video; and a prediction unit which inputs the recognized key points into an artificial intelligence model, segments the sign language into morphemes, and predicts position information of the segmented morphemes. Accordingly, by recognizing the morphemes of the sign language video frame by frame on the basis of a skeletal model and thereby segmenting the sign language into morphemes and predicting morpheme positions, it is possible to lay the foundations for accurate sign language translation.

公开(公告)号：US20240232919A9

公开(公告)日：2024-07-11

申请号：US18469381

申请日：2023-09-18

Applicant: KOREA ELECTRONICS TECHNOLOGY INSTITUTE

Inventor： Min Goo LEE ,  Yong Kuk PARK ,  Tae Heon NO

IPC: G06Q30/0203 ,  G06N20/20

CPC classification number: G06Q30/0203 ,  G06N20/20

Abstract: A system evaluates residential satisfaction of residents living in a building, based on preferred sections of the residents predicted using personal tendencies of the residents and sensing data collected through sensors in the building. The system may include a server that evaluates the residential satisfaction of the residents by analyzing a correlation between the sensing data and residential satisfaction information obtained from the survey conducted through a communication manner including the user terminals, and controls an air conditioning system in the building of a control target by predicting a feature-based preferred section of the users through random forest model learning.

公开(公告)号：US20240227855A9

公开(公告)日：2024-07-11

申请号：US18371198

申请日：2023-09-21

Applicant: Korea Electronics Technology Institute

Inventor： Dae Kyo SHIN ,  Ki Taeg LIM ,  Pu Sik PARK ,  Han Gyun JUNG ,  Sang Hun YOON ,  Soo Hyun JANG ,  Seong Hyun JANG ,  Jun Hyek JANG ,  Byoung Man AN

IPC: B60W60/00

CPC classification number: B60W60/0015 ,  B60W2554/402 ,  B60W2556/65

Abstract: There is provided a cooperative driving control method based on a vehicle security status. The cooperative driving method according to an embodiment includes: identifying a security status of a cooperative driving target vehicle; determining a cooperative driving strategy according to the identified security status; and controlling driving according to the determined cooperative driving strategy. Accordingly, cooperative driving may be performed or excluded based on a security status of a target vehicle, so that an accident may be prevented from being caused by cooperative driving with a problematic vehicle, and safety of a driver and an occupant may be guaranteed.

公开(公告)号：US20240222466A1

公开(公告)日：2024-07-04

申请号：US18523748

申请日：2023-11-29

Applicant: KOREA ELECTRONICS TECHNOLOGY INSTITUTE

Inventor： Byungwook YOO ,  Min Suk OH

IPC: H01L29/51 ,  H01L29/423 ,  H01L29/786

CPC classification number: H01L29/513 ,  H01L29/42384 ,  H01L29/78693

Abstract: Proposed is a thin film transistor that can be manufactured by a low-temperature process The thin film transistor can be manufactured at a low processing temperature and can be applied to various types of flexible substrates without deteriorating the device characteristics Also proposed are a manufacturing method to which a low processing temperature is applied as a fabricating method thereof, a semiconductor device and an electronic device including the same.

公开(公告)号：US20240221244A1

公开(公告)日：2024-07-04

申请号：US18498589

申请日：2023-10-31

Applicant: KOREA ELECTRONICS TECHNOLOGY INSTITUTE

Inventor： Jun Hwan JANG ,  Woo Chool PARK ,  Min Su CHOI ,  Jun Suk LEE ,  Bon Jae KOO

IPC: G06T11/00 ,  G06V10/56

CPC classification number: G06T11/001 ,  G06V10/56

Abstract: A system and a method for split-rendering for persons with color weakness are proposed. The split-rendering method may include, by a service server, in response to a login of a user device, loading a color weakness profile corresponding to a user of the logging-in user device. The method may also include, by the service server, in response to the user being color-weak in accordance with the loaded color weakness profile, selecting one of a plurality of split-rendering servers. The method may further include, by the service server, transmitting a video content along with the color weakness profile to the selected split-rendering server, and by the service server, transmitting access information about the selected split-rendering server to the user device.

公开(公告)号：US20240202951A1

公开(公告)日：2024-06-20

申请号：US18539832

申请日：2023-12-14

Applicant: Korea Electronics Technology Institute

Inventor： Min Gyu PARK ,  Ju Hong YOON ,  Min Ho LEE ,  Je Woo KIM

IPC: G06T7/593 ,  G01S17/89 ,  G06V10/771

CPC classification number: G06T7/593 ,  G01S17/89 ,  G06V10/771 ,  G06T2207/20081

Abstract: There is provided a depth estimation method for a small baseline-stereo camera through LiDAR sensor fusion. A depth map estimation method according to an embodiment may estimate a high-resolution depth map from a small baseline-stereo image based on deep learning, by using transfer learning from a deep learning network that is trained to estimate a depth map from a wide baseline-stereo image. Accordingly, in a device which has a small baseline-stereo camera installed therein due to structural constraints, such as a smartphone, a wearable AR/VR device, a drone, 3D image quality can be enhanced. In addition, according to embodiments, pseudo-LiDAR data may be generated by using a depth map estimated from a small baseline-stereo image, and may be used for replacing or reinforcing LiDAR data.

公开(公告)号：US20240193969A1

公开(公告)日：2024-06-13

申请号：US18536856

申请日：2023-12-12

Applicant: Korea Electronics Technology Institute

Inventor： Jae Woong YOO ,  Mi Ra LEE ,  Hye Dong JUNG

IPC: G06V20/70 ,  G06V10/44 ,  G06V10/74

CPC classification number: G06V20/70 ,  G06V10/44 ,  G06V10/761

Abstract: There is provided a method for creating multimodal training datasets for predicting characteristics of a user by using pseudo-labeling. According to an embodiment, the method may acquire a labelled dataset in which an image of a user is labelled with personality information and may extract a multimodal feature vector from the image of the acquired labelled dataset, may acquire an un-labelled dataset in which an image of a user is not labelled with personality information and may extract a multimodal feature vector from the image of the acquired un-labelled dataset, may measure a similarity between the extracted multimodal feature vector of the labelled dataset and the multimodal feature vector of the un-labelled dataset, and may label the un-labelled dataset based on the measured similarity. Accordingly, by creating multimodal training datasets for predicting a user personality by using pseudo-labeling, training datasets may be obtained rapidly, economically and effectively.