Samsung Electronics Co., Ltd.

Samsung Life Public Welfare Foundation

Sungkyunkwan University

Baek Hwan Cho

Keun Woo Park

Young Wan Seo

Paul Barom Jeon

Yeong Kyeong Seong

Qiang Wang

Kyoung Gu Woo

Ping Guo

Joo Hyuk Jeon

Dongqing Zou

Ye Hoon Kim

Hong-seok Lee

Jung Woo Kim

Youngwan Seo

Changhyun Kim

Joon Ah Park

Eric Hyunsurk Ryu

Jung Hoe Kim

Ha Young Kim

Jaehoon Cho

Jooyeon Woo

Hyoa Kang

Jin-Man Park

Changwoo Shin

Seung Hoon Han

Young Sang Cho

Hyoung Min Park

EricHyunsurk Ryu

Kyung Ah Park

Tae Sung Jung

Chae Jung Park

Derek Daehyun Ji

Won-Ho Chung

Kyoung Seok Pyun

Sei Yeul Oh

Moon Ho Park

Provided are a method and an apparatus for measuring an endolymphatic hydrops ratio of inner ear organs using an artificial neural network. The method of measuring an endolymphatic hydrops ratio includes obtaining a plurality of frame images obtained by capturing inner ear organs, obtaining a plurality of pieces of mask data corresponding to each of the plurality of frame images by inputting the plurality of frame images into a neural network, clustering the plurality of pieces of mask data according to the inner ear organs and obtaining representative images according to the inner ear organs according to certain conditions, and overlapping a target image synthesized by using the plurality of frame images and the representative images according to the inner ear organs so as to measure an endolymphatic hydrops ratio.

Method and apparatus for measuring endolymphatic hydrops ratio of inner ear organ using artificial neural network

A processor implemented image processing method includes recognizing a target object in a first frame of an input image; adjusting an exposure of a second frame of the input image based on a brightness of the target object; and generating a synthesized image by synthesizing the first frame and the second frame.

Image processing method for autonomous driving and apparatus thereof

An eye disease diagnosis method using artificial intelligence may include: collecting, from a database, a first eyeground image of a myopic patient who is not diagnosed with an eye disease and a second eyeground image of a myopic patient who has been diagnosed with the eye disease; learning eyeball change information by degree of myopia based on the first eyeground image, using deep learning; comparing and analyzing the first eyeground image and the second eyeground image based on the eyeball change information by the degree of myopia, and learning eyeball change information by the eye disease using deep learning; and estimating determination criteria of an eyeground image for diagnosis of the eye disease, based on a difference between the eyeball change information by the degree of myopia and the eyeball change information by the eye disease.

Eye disease diagnosis method and system using artificial intelligence

Disclosed is a method and apparatus of detecting an object approaching a vehicle, the method includes a user from the image, extracting feature points associated with the device or a portion of the user's body from the image of the user, detecting the object using a device based on the feature point, and issuing an alert of the approaching object.

Method and apparatus for informing pedestrian and occupant of vehicle of each other's approach

A method and apparatus for processing a binocular disparity image are provided. A method of determining a disparity of a binocular disparity image that includes a left eye image and a right eye image includes acquiring features of a plurality of pixels of the binocular disparity image based on an event distribution of the binocular disparity image, calculating a cost matrix of matching respective pixels between the left eye image and the right eye image based on the features, and determining a disparity of each matched pair of pixels based on the cost matrix.

Method and apparatus for processing binocular disparity image

Disclosed is a stereo camera-based autonomous driving method and apparatus, the method including estimating a driving situation of a vehicle, determining a parameter to control a stereo camera width of a stereo camera based on the estimated driving situation, controlling a capturer configured to control arrangement between two cameras of the stereo camera for a first direction based on the determined parameter, and measuring a depth of an object located in the first direction based on two images respectively captured by the two cameras with the controlled arrangement.

Stereo camera-based autonomous driving method and apparatus

A method and apparatus for detecting an error in gesture recognition are provided. The method includes sensing whether an effective gesture occurs in a first area for gesture recognition of a user; setting a second area and sensing an occurrence of an event due to a movement of the user, based on a result of the sensing in the first area; and detecting the error in the gesture recognition based on whether the occurrence of the event is sensed in the second area.

Method and apparatus for detecting error in gesture recognition

A method of visualizing anatomical elements in a medical includes receiving a medical image; detecting a plurality of anatomical elements from the medical image; verifying a location of each of the plurality of anatomical elements based on anatomical context information including location relationships between the plurality of anatomical elements; adjusting the location relationships between the plurality of anatomical elements; and combining the verified and adjusted information of the plurality of anatomical elements with the medical image.

Apparatus and method for visualizing anatomical elements in a medical image

A method and apparatus for acquiring an image disparity are provided. The method may include acquiring, from dynamic vision sensors, a first image having a first view of an object and a second image having a second view of the object; calculating a cost within a preset disparity range of an event of first image and a corresponding event of the second image; calculating an intermediate disparity of the event of the first image and an intermediate disparity of the event of the second image based on the cost; determining whether the event of the first image is a matched event based on the intermediate disparity of the event of the first image and the intermediate disparity of the event of the second image; and predicting optimal disparities of all events of the first image based on an intermediate disparity of the matched event of the first imaged.

Method and apparatus for acquiring image disparity

An event signal processing method and apparatus are provided. The event signal processing method includes receiving, from an event-based sensor, event signals including timestamps, generating a first timestamp map based on the timestamps, and interpolating a new timestamp into the first timestamp map based on at least two timestamps of the first timestamp map, to generate a second timestamp map.

Event signal processing method and apparatus

An electronic device for detecting a position of an object is disclosed, The electronic device includes an optical source configured to emit light to a detection area, a light concentrator configured to concentrate light reflected by a target object located in a detection area, a light receiver configured to receive through photodiodes the reflected light concentrated by the light concentrator and to output a light quantity pattern of the reflected light, and a processor configured to determine the position of the target object based on the light quantity pattern of the reflected light.

Device and method for detecting position of object

Disclosed are an image sampling apparatus and method. The image sampling apparatus includes a probe angular velocity detector configured to detect an angular velocity of a probe representing a change in an angle of the probe at a surface of an object, an image segmenter configured to receive the angular velocity and an image captured by the probe, and to segment the image into sub-regions based on the angular velocity, and a differential sampler configured to sample the sub-regions with a different sampling rate based on a position of a sub-region.

Apparatus and method for sampling images

Disclosed is region of interest (ROI) detection apparatus and method. The ROI detection apparatus includes: a selecting criterion acquirer configured to acquire a selecting criterion; an image receiver configured to receive a current image; a suspicious area selector configured to select a part of the current image as a suspicious area according to the selecting criterion; and an ROI detector configured to detect an ROI from the suspicious area.

System and method for detecting region of interest

An apparatus and a method for lesion detection are provided. The method of lesion detection involves detecting lesion candidates from a medical image, detecting anatomical objects from the medical image, verifying each of the lesion candidate based on anatomical context information comprising information regarding a location relationship between the lesion candidates and the anatomical objects, and removing one or more false positive lesion candidate from the detected lesion candidates based on a verification result.

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Seoul, South Korea

Baek Hwan Cho