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Patent Agency Ranking
公开(公告)号：US20210241450A1
公开(公告)日：2021-08-05
申请号：US17163051
申请日：2021-01-29
Inventor： Hye-Jin KIM , Suyoung CHI
Abstract: An apparatus for detecting a dimension error obtains an image of a target object, estimates dimensional data for a region of interest (ROI) for which dimensions are to be measured from the image of the target object using a learned dimensional measurement model, and determines whether there is a dimension error in the ROI from the estimated dimension data using a learned dimension error determination model.
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公开(公告)号：US20210225146A1
公开(公告)日：2021-07-22
申请号：US17121287
申请日：2020-12-14
Inventor： Sang-Won GHYME , Hye-Jin KIM , Seon-Ho OH , Geon-Woo KIM , Sang-Wook PARK , So-Hee PARK , Su-Wan PARK , Kyung-Soo LIM , Bum-Suk CHOI , Seung-Wan HAN , Jong-Wook HAN
Abstract: Disclosed herein are a method and apparatus for detecting a disaster based on images. The apparatus includes an image capture unit for capturing video using at least one camera and controlling the camera based on a camera control signal received from the outside; a disaster detection unit for generating a disaster log based on the video captured using the camera; a disaster analysis unit for calculating a disaster occurrence probability value based on the disaster log and determining whether to enter a camera control mode based on the disaster occurrence probability value; and a disaster alert unit for warning of a disaster based on a disaster alert request signal.
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3.发明申请公开(公告)号：US20200175353A1
公开(公告)日：2020-06-04
申请号：US16698711
申请日：2019-11-27
Inventor： Hye-Jin KIM , Sang-Yun OH , Jong-Eun LEE
IPC: G06N3/04
Abstract: Disclosed herein are a neural-network-lightening method using a repetition-reduction block and an apparatus for the same. The neural-network-lightening method includes stacking (accumulating) an output layer (value) of either one or both of a layer constituting a neural network and a repetition-reduction block in a Condensed Decoding Connection (CDC), and lightening the neural network by reducing a feature map, generated to correspond to data stacked in the CDC, based on a preset reduction layer.
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公开(公告)号：US20140099030A1
公开(公告)日：2014-04-10
申请号：US14021799
申请日：2013-09-09
Inventor： Hye-Jin KIM , Jae Yeon LEE
IPC: G06T7/00
Abstract: An apparatus for providing an object image recognition includes a boundary extraction unit to extract a boundary of an object image. A feature extraction module extracts a center point of the object image and at least one local feature point from the extracted boundary and calculates each distance between the extracted center point and the extracted local feature point.
Abstract translation: 用于提供对象图像识别的装置包括提取对象图像的边界的边界提取单元。 特征提取模块从提取的边界提取对象图像的中心点和至少一个局部特征点，并计算提取的中心点和提取的局部特征点之间的每个距离。
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5.发明申请DEPTH INFORMATION EXTRACTING METHOD BASED ON MACHINE LEARNING AND APPARATUS THEREOF 审中-公开基于机器学习的深度信息提取方法及其设备公开(公告)号：US20170069094A1
公开(公告)日：2017-03-09
申请号：US15256447
申请日：2016-09-02
Inventor： Hye-Jin KIM
CPC classification number: G06T7/529 , G06K9/00208 , G06K9/627 , G06T2207/10024 , G06T2207/20081
Abstract: The disclosure relates to a method and an apparatus for extracting depth information from an image. A method for extracting depth information based on machine learning according to an exemplary embodiment of the present disclosure includes generating a depth information model corresponding to at least one learning image by performing machine learning using the at least one learning image and a plurality of depth information corresponding to the at least one learning image; and extracting depth information of a target image by applying the depth information model into the target image. Embodiments of the disclosure may allow extracting precise depth information from a target image.
Abstract translation: 本发明涉及从图像中提取深度信息的方法和装置。 根据本公开的示例性实施例的用于提取基于机器学习的深度信息的方法包括通过使用所述至少一个学习图像执行机器学习来生成对应于至少一个学习图像的深度信息模型，以及对应于所述至少一个学习图像的多个深度信息 至少一个学习图像; 以及通过将深度信息模型应用到目标图像中来提取目标图像的深度信息。 本公开的实施例可以允许从目标图像提取精确的深度信息。
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