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公开(公告)号:US20190332625A1
公开(公告)日:2019-10-31
申请号:US16246707
申请日:2019-01-14
Inventor: Keun Dong LEE , Seung Jae LEE , Jong Gook KO , Hyung Kwan SON , Weon Geun OH , Da Un JUNG
IPC: G06F16/532 , G06K9/00 , G06K9/46 , G06K9/62 , G06F16/583 , G06F16/51
Abstract: An apparatus and method for searching for a building on the basis of an image and a method of constructing a building search database (DB) for image-based building search. The method includes constructing a building search DB, receiving a query image from a user terminal, detecting a region to which a building belongs in the query image, extracting features of the region detected in the query image, and searching the building search DB for a building matching the extracted features. Therefore, building search performance can be improved.
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公开(公告)号:US20180315108A1
公开(公告)日:2018-11-01
申请号:US15959454
申请日:2018-04-23
Inventor: Weon Geun OH , Jong Gook KO , Da Un JUNG , Seung Jae LEE , Hyung Kwan SON , Keun Dong LEE
Abstract: An omni-channel management method includes receiving a distribution channel information and a product purchase information from each of a plurality of distribution channels, and integrating the received distribution channel information and the product purchase information; applying an image identification technology and a voice identification technology to retrieve and integrate information related to a product; receiving and integrating product information from a manufacturer, a seller, or a web site; verifying consistency of the integrated product information by checking whether detailed information included in the integrated product information is related to a same product; and providing the consistency-secured product information to a consumer and a plurality of distribution channels.
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公开(公告)号:US20170199900A1
公开(公告)日:2017-07-13
申请号:US15332136
申请日:2016-10-24
Inventor: Seung Jae LEE , Keun Dong LEE , Hyung Kwan SON , Weon Geun OH , Da Un JUNG , Young Ho SUH , Wook Ho SON , Won Young YOO , Gil Haeng LEE
CPC classification number: G06F16/5866 , G06F16/248 , G06F16/29 , G06F16/51 , G06K9/00704 , G06K9/4671 , G06K9/52 , G06K9/6201 , G06K9/6211 , G06K9/6267 , G06K2009/4666 , G06N20/00 , G06T2207/20021 , G06T2207/20076 , G06T2215/16
Abstract: A server for providing a city street search service includes a street information database configured to store city street images, a feature selection unit configured to select at least one feature according to a predetermined criterion when a city street image for searching and two or more features for the image are received from a user terminal, a candidate extraction unit configured to extract a candidate list of a city street image, a feature matching unit configured to match the city street image for registration included in the extracted candidate list and the at least one selected feature, and a search result provision unit configured to provide the user terminal with a result of the matching as result information regarding the city street image for searching.
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公开(公告)号:US20180189596A1
公开(公告)日:2018-07-05
申请号:US15835662
申请日:2017-12-08
Inventor: Seung Jae LEE , Hyung Kwan SON , Keun Dong LEE , Jong Gook KO , Weon Geun OH , Da Un JUNG
CPC classification number: G06K9/4642 , G06K9/3233 , G06K9/6267 , G06K9/6271 , G06N20/00 , G06T2210/12
Abstract: A machine learning method for learning how to form bounding boxes, performed by a machine learning apparatus, includes extracting learning images including a target object among a plurality of learning images included in a learning database, generating additional learning images in which the target object is rotated from the learning images including the target object, and updating the learning database using the additional learning images.
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公开(公告)号:US20170206646A1
公开(公告)日:2017-07-20
申请号:US15235152
申请日:2016-08-12
Inventor: Da Un JUNG , Keun Dong LEE , Seung Jae LEE , Hyung Kwan SON , Weon Geun OH
CPC classification number: G06T7/0004 , G06F17/30256 , G06F17/30271 , G06F17/3028 , G06K9/342 , G06K9/4604 , G06K9/6218 , G06K2209/17 , G06T2207/30128
Abstract: An apparatus for food search service includes a food region extractor configured to perform detection in regions in an image where food is present and extract a plurality of candidate regions; a candidate region refiner configured to cluster the candidate regions into groups according to a ratio of overlap between the candidate regions; and a search result generator configured to determine a position of a food region and a food item from the grouped candidate regions.
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