• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.272-275
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• 2004

Recently, the services using position information of moving objects is embossed. Theses services needs the moving objects databases to manage moving object data with efficiency. To build the moving object databases, we must develop the moving object engine to mange, store, and search the spatio temporal data of moving object. The moving object engine has to support query syntax to search data that suitable for user need like LBS, Telematics, ITS, vehicle management system. In this paper, we design and implement the moving object engine to support service with moving object data. The moving object engine is able to support system environment that users are able to get the moving object data easily even they don't know complex data structure.

• 한국컴퓨터산업학회논문지
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• 제10권3호
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• pp.73-78
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• 2009

This paper designed Object-orientid Meta_data operation module that introducted new Meta_class basis the Meta_Classfication model. In order to implement this Data model, we have introducted heurilistic class to traditional object-orinted database. And we designed Meta_data operation module for Inplemetated Meta_data that basis on the heurilistic classficasion model using stored Meta_data in extened object-oriend data model.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.518-523
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• 2008

In this study, we analyzed applicability of object database, designed the concept model based on object-oriented idea for measurement data management, and applied the design model to object database. The concept model composes three sub models Infrastructure managing information model, Infrastructure measurement data model, and Measurement unit model. The process to expand measurement data of new type was executed easily without changing database schema in object database. The process to expand measurement data of new type was executed easily without changing database schema in object database. Therefore, applicability of new technology to infrastructures for building a safety management network of road bridges could be increased with object database system.

• 한국컴퓨터정보학회논문지
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• 제22권5호
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• 한국통신학회논문지
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• 제8권1호
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• pp.23-29
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• 1983

본 논문은 신뢰성과 abstract data type을 효과적으로 뒷받침할 수 있도록 object에 기초를 둔 운영체제의 구성에 대하여 논하였다. 신뢰성을 위하여 모든 object는 capability에 의해서만 access가 가능하도록 access right을 규정하였으며 모든 program 모듈은 protection domain을 갖도록 하여 이에 대한 효율적인 domain변경이 제시되었다. 또한 abstract data type을 위하여 type manager를 이용하였다.

• 한국전자거래학회지
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• 제4권1호
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• pp.145-157
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• 1999

The challenge is to maximize the time-to-market benefits of concurrent engineering while maintaining control of data and distributing it automatically to the people who need it when they need it. The way PDM systems cope with this challenge is that master data is held only once in a secure vault where its integrity can be assured and all changes to it monitored, controlled and recorded. The structure of PDM is various from vendor, but they have common module. That is PDM and it is most important. The goal is to design the workflow in PDM using object-oriented modeling method. The past methods have concentrated on the flow between workflow engine and agent, but this paper will focus on task. We will model task as individual object. This paper uses OMT(Object Modeling Technique) by James Rumbaugh for base modeling tool and uses DCOM(Distributed Component Object Model) for base ORB(Object Request Broker). Research object is to design the static object model, to design state change by dynamic model and to design data transition by functional model.

• 한국정보처리학회논문지
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• 제7권4호
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• pp.1050-1061
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• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• 한국군사과학기술학회지
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• 제25권3호
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• pp.300-310
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• 2022

A vast amount of labeled data is required for deep neural network training. A typical strategy to improve the performance of a neural network given a training data set is to use data augmentation technique. The goal of this work is to offer a novel image augmentation method for improving object detection accuracy. An object in an image is removed, and a similar object from the training data set is placed in its area. An in-painting algorithm fills the space that is eliminated but not filled by a similar object. Our technique shows at most 2.32 percent improvements on mAP in our testing on a military vehicle dataset using the YOLOv4 object detector.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.251-252
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• 2023

As technology improves with the 4th industrial revolution, smart construction is becoming a key part of safety management in the architecture and civil engineering. By using object detection technology with CCTV data, construction sites can be managed efficiently. In this study, super resolution technology based on deep learning is proposed to improve the accuracy of object detection in construction sites. As the resolution of a train set data and test set data get higher, the accuracy of object detection model gets better. Therefore, according to the scale of construction sites, different object detection models can be considered.

• 대한원격탐사학회지
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• 제23권3호
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• pp.153-160
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• 2007

Forest cover density studies using high resolution satellite data and object oriented classification are limited in India. This article focuses on the potential use of QuickBird satellite data and object oriented classification in forest density mapping. In this study, the high-resolution satellite data was classified based on NDVI/pixel based and object oriented classification methods and results were compared. The QuickBird satellite data was found to be suitable in forest density mapping. Object oriented classification was superior than the NDVI/pixel based classification. The Object oriented classification method classified all the density classes of forest (dense, open, degraded and bare soil) with higher producer and user accuracies and with more kappa statistics value compared to pixel based method. The overall classification accuracy and Kappa statistics values of the object oriented classification were 83.33% and 0.77 respectively, which were higher than the pixel based classification (68%, 0.56 respectively). According to the Z statistics, the results of these two classifications were significantly different at 95% confidence level.