• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.115-121
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• 2009

Today, many studies are conducted on searching for criminals in railroad stations using intelligent surveillance system. In the 1st stage, this study conducted a simulation of the system which searches for a criminal using a DB containing information on former convicts (DB on high risk former convicts), when a crime has taken place in a railroad station. Then, in the 2nd stage, this study has developed a simulation that can search for people who is wearing the same color clothes as the criminal and are found near the station, once the color of clothes of the criminal has been entered.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.96-107
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• 1996

In case of remote image retrieval via shared network or low speed link in order to make a decision for target image problems such as transmission delay are encountered. In this paper browsing and optimization techniques are proposed for fast retrieval of Image by the multiresolution representation and progressive transmission. The proposed network model was analyzed and evaluated for system's performance improvement. Interactive user-system using several multiresolution representation has shown better performance in transmission delay minimization over the single resolution image retrieval system.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.1-9
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• 2021

Deep learning in computer vision has made accelerated improvement over a short period but large-scale learning data and computing power are still essential that required time-consuming trial and error tasks are involved to derive an optimal network model. In this study, we propose a similar image classification performance improvement method based on CR (Confusion Rate) that considers only the characteristics of the data itself regardless of network optimization or data reinforcement. The proposed method is a technique that improves the performance of the deep learning model by calculating the CRs for images in a dataset with similar characteristics and reflecting it in the weight of the Loss Function. Also, the CR-based recognition method is advantageous for image identification with high similarity because it enables image recognition in consideration of similarity between classes. As a result of applying the proposed method to the Resnet18 model, it showed a performance improvement of 0.22% in HanDB and 3.38% in Animal-10N. The proposed method is expected to be the basis for artificial intelligence research using noisy labeled data accompanying large-scale learning data.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.358-375
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• 1997

가. 패션 디자인 기초 정보 수집/분석 - 국내외에 산재하는 패션디자인 정보의 기초자료를 입수 - 디자이너별/ 컬렉션별/주제별로 분류 - 가공 나- 패션디자인정보의 멀티미디어 DATA BASE개발 - 화상(IMAGE)/해설(TEXT)/ SOUND의 복합 DATA BASE SYSTEM - PC통신망 서비스를 위한 DATA개발 다. 패션디자인 관련자료의 DB화 - 패션디자인 이론서 - 패션디자인 컨테스트 / 이벤트 정보 - 패션디자인 교육기관 정보 - 패션브랜드 정보 (내셔널 / 디자이너 / 수입) 라. DATA BASE 공급 서비스 - PC통신망을 통한 서비스(DOWN LOAD 가능) - 디자인작품 IMAGE 및 CONCEPT/ DETAILS/ CAPTION - PC통신을 이용 디자인 인력 구인/구직정보 활용 - 패션디자인 해외유학 정보 마. Inter-NET 서비스 - Inter-NET을 이용 국내디자이너작품 해외 소개(중략)

• Proceedings of the Korea Society of Design Studies Conference
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• 1999.05a
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• pp.36-37
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• 1999

디자인 프로세스상에 이미지를 중심으로 하는 시각언어를 통한 디자인 컨셉 커뮤니케이션은 이미 여러 디자인분야에서 여러 가지 방향으로 진행되고 있다(스타일 스케치보드, 이미지 맵, 컬러맵, 캐털로그 리뷰 등). 그러나 대부분의 경우, 디자인 리서치에 사용되어진 이미지들은 리서치 이후 저장되지 않고 폐기되어지기 때문에, 새로운 디자인 작업에서 재활용되어지지 못하는 프로세스상의 단점을 가지고 있다.(중략)

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.225-228
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• 2001

We propose a method which has effective scalable indexing characteristics of large color image archives. Color key and energy key method which uses provides high performance of fast accessing and has almost constant query response time over DH size.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.9-17
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• 2017

This paper describes a process of developing commercial real time image recognition system with company. In this paper we will make a system that is combining an empirical kernel map method and conjugate least squares support vector machine in order to represent images in a low-dimensional subspace for real time image recognition. In the traditional approach calculating these eigenspace models, known as traditional PCA method, model must capture all the images needed to build the internal representation. Updating of the existing eigenspace is only possible when all the images must be kept in order to update the eigenspace, requiring a lot of storage capability. Proposed method allows discarding the acquired images immediately after the update. By experimental results we can show that empirical kernel map has similar accuracy compare to traditional batch way eigenspace method and more efficient in memory requirement than traditional one. This experimental result shows that proposed model is suitable for commercial real time image recognition system.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.37-58
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• 2011

In general, testing DB applications is much more difficult than testing other types of software. The fact that the DB states as much as the input data influence and determine the procedures and results of program testing is one of the decisive reasons for the difficulties. In order to create and maintain proper DB states for testing, it not only takes a lot of time and efforts, but also requires extensive IT expertise and business knowledge. Despite the difficulties, there are not enough research and tools for the needed help. This article reports the result of research on automatic creation and maintenance of DB states for testing DB applications. As its core, this investigation develops an automation tool which collects relevant information from a variety of sources such as log, schema, tables and messages, combines collected information intelligently, and creates pre- and post-Images of database tables proper for application tests. The proposed procedures and tool are expected to be greatly helpful for overcoming inefficiencies and difficulties in not just unit and integration tests but including regression tests. Practically, the tool and procedures proposed in this research allows developers to improve their productivity by reducing time and effort required for creating and maintaining appropriate DB sates, and enhances the quality of DB applications since they are conducive to a wider variety of test cases and support regression tests. Academically, this research deepens our understanding and introduces new approach to testing enterprise systems by analyzing patterns of SQL usages and defining a grammar to express and process the patterns.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.97-105
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• 2020

Recently, for a smart city, there is a demand for a technology for acquiring traffic information using an intelligent road infrastructure and managing it. In the meantime, various technologies such as loop detectors, ultrasonic detectors, and image detectors have been used to analyze road traffic information but these have difficulty in collecting various informations, such as traffic density and length of a queue required for building a traffic information DB for moving vehicles. Therefore, in this paper, assuming a smart city built on the basis of a camera infrastructure such as intelligent CCTV on the road, a solution for calculating the traffic DB of moving vehicles using Vision Tracking of road CCTV cameras is presented. Simulation and verification of basic performance were conducted and solution can be usefully utilized in related fields as a new intelligent traffic DB calculation solution that reflects the environment of road-mounted CCTV cameras and moving vehicles in a variable smart city road environment. It is expected to be there.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.