• The KIPS Transactions:PartB
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• v.8B no.4
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• pp.335-342
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• 2001

본 논문은 보로노이 공간분류를 활용하여 원격탐사 영상인식을 위한 다층 신경망 분류기를제안한다. 제안된 다층 신경망 분류기는 보로노이 다각형 영역으로 클래스를 구분하며, 초평면 방정식의 계수를 오류 역전과 학습 초기의 연결 강도, 임계치 그리고 은닉층의 노드 수로 결정한다. 제안된 방법은 오류역전과 학습 알고리즘에서 임의로 정해주던 초기 정보를 사전 분석에 의해 공학적으로 결정함으로써 느린 수렴 속도와 학습실패 등의 단점을 피할 수 있는 장점이 있다. 보로노이 다이어그램에 대한 경계선의 초평면 방정식은 훈련집합의 클래스별 평균값을 구하여 Mathematica 패키지로 계산하였다. 제안된 다층 신경망에 의한 영상분류기의 인식능력을 평가하기 위하여 원격탐사 영상인식에서 자주 활용되는 최소거리 분류 방법과 최대우도 분류 방법으로 처리해서 비교한 결과, 최소거리 분류 방법은 실험화상에 대해 81.4%, 최대우도 부류기에 의한 분류는 87.8%, 제안한 방법은 92.2% 정확성을 가진 분류결과를 나타냈다.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.896-913
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• 2018

Seam finding algorithm is one of the most important techniques to construct the high quality 360 VR image. We found that some degradations, such as ghost effect, are generated when the conventional seam finding algorithms (for examples, Voronoi algorithm, Dynamic Programming algorithm, Graph Cut algorithm) are applied, because those make the inefficient masks which cross the body of main objects. In this paper, we proposed an advanced seam finding algorithm providing the efficient masks which go through background region, instead of the body of objects. Simulation results show that the proposed algorithm outperforms the conventional techniques in the viewpoint of the quality of the stitched image.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.822-827
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• 2003

Topological maps have drawn more attention recently because they are compact, provide natural interfaces, and are applicable to path planning easily. To build a topological map incrementally, Voronoi diagram was used by many researchers. The Voronoi diagram, however, has difficulty in applying to arbitrarily shaped objects and needs long computation time. In this paper, we present a new method for global topological map from the local topological maps incrementally. The local topological maps are created through a thinning algorithm from a local grid map, which is built based on the sensor information at the current robot position. A thinning method requires simpler computation than the Voronoi diagram. Localization based on the topological map is usually difficult, but additional nodes created by the thinning method can improve localization performance. A series of experiments have been conducted using a two-wheeled mobile robot equipped with a laser scanner. It is shown that the proposed scheme can create satisfactory topological maps.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.2
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• pp.109-122
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• 2019

The purpose of this study is to examine the clothing component information and attributes as the control parameters for the 3D modeling process of the biomorphic clothing sculpture using a parametric methodology. The 3D modeling parameters of biomorphic clothing sculpture were identified as exaggerated silhouette, surface texture, and digital color. The types of exaggerated silhouettes were shoulder and hip exaggeration, shoulder exaggeration, hip exaggeration, vertical exaggeration, and horizontal exaggeration. The types of surface texture were embossed, lacy, furry, and complex textures. The types of digital color were chrome, blur, blend, and acid colors. The characteristics of morphological representation due to the attributes of these control variables were identified as morphological variation, organic morphology, organizational morphology, and realistic morphology. As a result, it was found that the parameter attributes were applied to the biomorphic clothing sculpture parametric design process and developed into various shapes.