• Journal of IKEEE
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• v.27 no.3
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• pp.280-287
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• 2023

Deep learning advancements can solve computer vision problems, but large-scale datasets are necessary for high accuracy. In this paper, we propose an image generation technique using object bounding boxes and image edge components. The object bounding boxes are extracted from the images through object detection, and image edge components are used as input values for the image generation model to create new image data. As results of experiments, the images generated by the proposed method demonstrated similar image quality to the source images in the image quality assessment, and also exhibited good performance during the deep learning training process.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.120-128
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• 2007

In order to reduce the lead-time and cost, the technology of rapid prototyping(RP) has been widely used. This paper describes the methodology to fabricate a large object by using the principle of rapid prototyping. By laminating thick and sloping polystyrene foam plates, we can make the large model which has three dimensional, continuous surfaces faster and easier than conventional processes. Estimated error was much smaller than other RP products which have stepped effect. For accuracy improvement and post processing, machined metal plates are added between the thick plates. To keep the continuity of surface and strengthen the model, pilot holes and guide rods are applied. By the methodology described in this paper, a missile body with flush air intake was fabricated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.503-509
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• 2001

For efficiently providing distributed services, distributed computing environments are specified the requirements of various services and distributed object platforms applied an object-oriented technology by TINA Consortium and OMG CORBA. Because applications are becoming large and distributing, their servicing and managing interfaces among objects are being complicated. In order to solve these defects, it is necessary to suggest a new object grouping model and specify object service/management requirements can be introduced under the object groups.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.299-313
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• 1995

Object-Oriented design method decomposes the program into object that establish the relationship between objects. It is the technique of object centered decomposition unlike function oriented legacy system. Since existing Object- Oriented design method doesn't fully explain of the design method of module and decomposition, and need to implement the Object-Oriented software as a total system init. It has many problems that whole object design method and application programs should be analyzed for the understanding an Object-Oriented software component. Therefore, this study provides a procedure for Object-Oriented module design and criteria of decomposition to practically support the complex and large system development. Futhermore, it shows a consistency between design model and implementation through a case study applying these module decomposition criteria to the real system.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.29-34
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• 2005

DNA microarray becomes a major tool for the investigation of global gene expression in all aspects of cancer and biomedical research. DNA microarray experiment generates enormous amounts of data and they are meaningful only in the context of a detailed description of microarrays, biomaterials, and conditions under which they were generated. MicroArray Gene Expression Data (MGED) society has established microarray standard for structured management of these diverse and large amount data. MGED MAGE-OM (MicroArray Gene Expression Object Model) is an object oriented data model, which attempts to define standard objects for gene expression. To assess the relevance of DNA microarray analysis of cancer research it is required to combine clinical and genomics data. MAGE-OM, however, does not have an appropriate structure to describe clinical information of cancer. For systematic integration of gene expression and clinical data, we create a new model, Cancer Genomics Object Model.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.461-470
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• 2004

This paper is to design the user interface of the groundwater well based on an object oriented. In order to implementation geographic data base of the an complex geo-object of the real world, this paper is the study of analysis pattern at the level By specifying the pattern appropriate to the application domain and designing the analysis pattern using the UML based on the object oriented methodology, this paper shall contribute to enhance the reuse of components that can develop and distribute a large scale open system.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.2
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• pp.130-139
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• 1998

The finite element analysis program should be prepared to deal with many of newly arising engineering problems. The sequential structured programming technique does not make a finite element method so flexible. So far, the object oriented programming technique was studied as an alternative programming paradigm. However, most of the research were in the state of the evaluation of the possibility and the applicability of the object oriented method for a finite element program. In this study, a practical object oriented finite element analysis program, OOFE_ JAVA was developed and the result of the analysis on a rectangular clamped plate was shown. The objects which compose the OOFE_JAVA were applied to several engineering problem without any modification and it was concluded that the object oriented technique was appropriate for the development of a complex and large engineering system. And a virtual machine which Java language is using can be loaded on any kinds of computer which has java interpreter regardless of the platform on which the OOFE_JAVA was developed.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.33-42
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• 2018

Object classification and detection are fundamental technologies in computer vision and its applications. Recently, a deep-learning based approach has shown significant improvement in terms of object classification and detection. This report reviews the progress of deep-learning based object classification and detection in views of the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), and analyzes recent trends of object classification and detection technology and its applications.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.661-664
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• 1998

Since the region segmentation at high resolution contains most of viable semantic object contours in an image, the bottom-up approach for image segmentation is appropriate for the application such as MPEG-4 which needs to preserve semantic object contours. However, the conventioal region merging methods, that follow the region segmentation, have poor performance in keeping low-contrast semantic object contours. In this paper, we propose an image segmentation algorithm based on classified region merging. The algorithm pre-segments an image with a large number of small regions, and also classifies it into several classes having similar gradient characteristics. Then regions only in the same class are merged according to the boundary weakness or statisticsal similarity. The simulation result shows that the proposed image segmentation preserves semantic object contours very well even with a small number of regions.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.399-404
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• 1992

Curved 3D objects represented by range data contain large amounts of information compared with planar objects, but do not have distinct features for matching to those of object models. This makes it difficult to represent and identify a general 3D curved object. This paper introduces a new approach to representing and finding a holdsite of general 3D curved objects using range data. We develop a three-dimensional generalized Hough transformation which can be also applied to general 3D curved object recognition and which reduces both the computation time and storage requirements. Our approach makes use of the relative geometric differences between particular points on the object surface and some model points which are prespecified arbitrarily and task dependently.