Samsung Electronics Co., Ltd.

Hyundai Motor Company

Kia Motors Corporation

Korea Advanced Institute of Science and Technology

Industry-University Cooperation Foundation Hanyang University

K. C. Tech Co., Ltd.

Dongchan Kim

Shin Ae Jun

Jinyoung Hwang

Dongnam Byun

Dae Hyun Kim

Taeyoung Kim

Tae Ho Kim

Taehyung Kim

Haedong Yeo

Jisoo Lee

Jongmyeong Ban

Jaeyeop Lee

Hyechan Bae

Junghwan Huh

Euiju Kim

Seongwo Oh

Jaehong Park

Je-Woo Han

Junho Yoon

Moorym Choi

Bongyong Lee

Gyungjin Min

Ae-Jeong Lee

Seunghoon Park

Sang-Hoon Kim

Hyun Wook Park

Janghee Park

Jinyoung Park

JungChak Ahn

Changhwa Kim

Jaewoong Choi

Taeyon Lee

Eunsung Seo

Jaesung Sim

Sang-Su Park

Beomsuk Lee

Doowon Kwon

Keunhee Bai

Minho Jang

Kinam Kwon

Hajin Lim

Jun Ha Hwang

Sungkweon Baek

Jaewook Shin

Kwansik Kim

Bo Yun Kim

Kyohyeok Kim

Soonmin Cha

Sung Pyo Lee

Kisoo Chang

Kyungyub Jeon

Chang Gil Kwon

Sungyeon Kim

Minjoon Park

Kyungrae Byun

Yongmoon Jang

Seongwoo Oh

Hyunseok Seo

Bokwon Kim

Enjung Kim

Seohee So

Kunsoo Huh

JongHyeok Park

Jae Jin Cho

You Jung Chung

Hyunyoung Yeo

Hong Kyu Seo

Provided is an electronic device configured to perform an operation corresponding to a user input by using an artificial intelligence model, and a method performed by the electronic device, of performing the operation. The method comprises obtaining touch data related to a touch input of a user, identifying a first training data set similar to the touch data from a plurality of pre-stored training data sets, training an artificial intelligence model based on the first training data set, identifying a type of a user input that is input to the electronic device, based on the trained artificial intelligence model, and performing an operation corresponding to the identified type of the user input.

Personalized electronic device inferring user input, and method for controlling same

A method of generating a three-dimensional (3D) model and a device for generating a 3D model are provided. The method includes generating a base 3D model of an object, determining a first target 3D model similar to the base 3D model from a 3D model database storing a plurality of 3D models, generating a first synthesized 3D model, determining a first similarity between the first synthesized 3D model and the at least one object image, determining a component having a low similarity between the first synthesized 3D model and the at least one object image, determining, as a second target 3D model, a 3D model having a high similarity to the first synthesized 3D model with respect to the component having the low similarity, from the 3D model database, and generating a second synthesized 3D model.

Method and electronic device for generating three-dimensional (3D) model

A method performed by an electronic device, includes: A method for performed by an electronic device, includes: acquiring an image by using a first lens; inputting information about a plurality of candidate regions of the image into a neural network model that is trained to acquire a score indicating whether a face of a person is included, and acquiring scores for the plurality of candidate regions; identifying a candidate region including at least part of a person's face among the plurality of candidate regions based on the acquired scores; and providing guide information for changing a capturing composition based on information about the location of the identified person region and a score of the identified person region.

Electronic device and method for controlling the electronic device

An electronic device and a controlling method of the electronic device are provided. The controlling method of an electronic device according to the disclosure includes the steps of, based on a first user input for or related to acquiring a live view image through a camera including a plurality of lenses different from one another being received, acquiring a plurality of image frames for each of the plurality of lenses and storing the image frames in a first memory, inputting the plurality of image frames for each lens stored in the first memory into a neural network model, by a predetermined time interval, and acquiring score information including composition preference information of each of the input image frames, selecting at least one lens among the plurality of lenses based on the score information, storing image frames acquired through the selected at least one lens in a second memory during the predetermined time interval, and based on a second user input for initiating recording of the live view image being received, storing an image related to the image frames stored in the second memory in a third memory until a time point when a third user input for ending the recording is received.

Electronic device and controlling method of electronic device

Disclosed are three-dimensional semiconductor memory devices and methods of detecting electrical failure thereof. The three-dimensional semiconductor memory device includes a substrate with a first conductivity including a cell array region and an extension region having different threshold voltages from each other, a stack structure on the substrate and including stacked electrodes, an electrical vertical channel penetrating the stack structure on the cell array region, and a dummy vertical channel penetrating the stack structure on the extension region. The substrate comprises a pocket well having the first conductivity and provided with the stack structure thereon, and a deep well surrounding the pocket well and having a second conductivity opposite to the first conductivity.

Three-dimensional semiconductor memory device and method of detecting electrical failure thereof

An electronic device includes a touch screen and a processor configured to: based on a touch input of a user being acquired through the touch screen, acquire an image corresponding to the acquired touch input of the user; identify a type of the acquired touch input of the user by inputting, to a neural network model for identifying the type of the touch input of the user, the acquired image, a first image corresponding to a first type touch input obtained by touching the touch screen with a pressure smaller than a preconfigured pressure, and a second image corresponding to a second type touch input obtained by touching the touch screen with a pressure greater than the preconfigured pressure; and perform a function based on the identified type of the touch input.

Device and method with trained neural network to identify touch input

Provided is a method of identifying a touch type of a user touch input with respect to an electronic device, the method including: obtaining touch data from a touch input received from a user; determining a touch recognition model set consisting of touch recognition models to be used to identify a touch type of the touch input of the user from among a plurality of touch recognition models corresponding to a plurality of partial time periods included in a time in which the touch input is maintained; obtaining touch type probability values with respect to the touch input of the user by applying the touch data to the touch recognition models included in the touch recognition model set; and identifying a touch type of the touch input, based on the obtained touch type probability values.

Electronic device and operating method of the same

A semiconductor device includes a substrate, a gate trench in the substrate, a gate insulating film in the gate trench, a titanium nitride (TiN)-lower gate electrode film on the gate insulating film, the titanium nitride (TiN)-lower gate electrode film including a top surface, a first side surface, and a second side surface opposite the first side surface, a polysilicon-upper gate electrode film on the titanium nitride (TiN)-lower gate electrode film, and a gate capping film on the polysilicon-upper gate electrode film. A center portion of the top surface of the titanium nitride (TiN)-lower gate electrode film overlaps a center portion of the polysilicon-upper gate electrode film in a direction that is perpendicular to a top surface of the substrate, and each of the first side surface and the second side surface of the titanium nitride (TiN)-lower gate electrode film is connected to the gate insulating film.

Semiconductor device and method of forming the same

An image sensor chip includes a lower chip, an upper chip stacked on the lower chip and including a photoelectric element, a via hole penetrating through the upper chip and penetrating through at least a portion of the lower chip, and a conductive connection layer electrically connecting the lower chip and the upper chip to each other in the via hole. The upper chip includes an upper substrate, an upper isolation layer and an upper element on the upper substrate, a connection contact plug, and a multilayer interconnection line electrically connected to the connection contact plug. A distance between an upper surface of the connection contact plug and an upper surface of the upper isolation layer is greater than a distance between an upper surface of an upper gate electrode of the upper element and an upper surface of the upper isolation layer.

Image sensor chip

An image sensor and a method of fabricating the image sensor, the image sensor including a semiconductor substrate having a first floating diffusion region, a molding pattern over the first floating diffusion region and including an opening, a first photoelectric conversion part at a surface of the semiconductor substrate, and a first transfer transistor connecting the first photoelectric conversion part to the first floating diffusion region. The first transfer transistor includes a channel pattern in the opening and a first transfer gate electrode. The channel pattern includes an oxide semiconductor. The channel pattern also includes a sidewall portion that covers a side surface of the opening, and a center portion that extends from the sidewall portion to a region over the first transfer gate electrode.

Image sensor including transfer transistor having channel pattern on interlayered insulating layer over substrate and method of fabricating an image sensor

A semiconductor device includes a substrate including an active region, a gate trench disposed in the substrate and crossing the active region; a gate dielectric layer disposed in the gate trench; a first gate electrode disposed on the gate dielectric layer and including center and edge portions; a second gate electrode disposed on the first gate electrode; a gate capping insulating layer disposed on the second gate electrode and filling the gate trench; and first and second impurity regions disposed in the substrate opposite to each other with respect to the gate trench. A top surface of each of the center and edge portions contacts a bottom surface of the second gate electrode. The top surface of the second gate electrode is concave. The bottom surface of the gate capping insulating layer is convex, and a side surface of the gate capping insulating layer contacts the gate dielectric layer.

Described herein are chemical mechanical polishing (CMP) slurry compositions, such as CMP slurry compositions for polishing an indium tin oxide (ITO) layer, along with methods of fabricating a semiconductor device using such a CMP slurry composition. The CMP slurry composition can include a polishing particle, a dispersing agent, an auxiliary oxidizing agent, and a sugar alcohol compound.

CMP slurry compositions and methods of fabricating a semiconductor device using the same

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Seoul, South Korea

Dongchan Kim