• 한국자동차공학회논문집
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• 제7권5호
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• pp.162-171
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• 1999

The most important part in automated transport systems is steering control for lane keeping Most of systems developed so far have used the visual information for steering control. In this study, the steering control algorithm based on visual servoing has been developed and tested by applying it on Radio Controlled(R/C) model car equipped with one CCD camera. We also demonstrated the feasibility of using it as a pre-test car before the real car experiment in developing automated vehicles. In order to solve the problem of the limited spave and load of a model car, remote-brained approach has been taken. For steering control of a model car, the PD controller which uses the look ahead offset to generate control input has been implemented and the characteristics of the controller has been explained in view of kinematics. Some experimental results have been also illustrated so as to show the control performance and stability.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.53-53
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• 2002

According to glowing computing capacity, software in remote sensing has supported diverse processing interfaces from batch interface to high-end user interactive interface. In this paper, component based visual modeler is developed to process batch jobs for high-end users as well as novices. Visual modeler arranges several node groups which are categorized according to their purposes. These nodes carry out elemental unit processes and can be grouped to model. The model represents user specified job which is composed diverse nodes. User can organize models by connecting diverse nodes according to data flow model specification which rules node's connectivity and direction, etc. Furthermore, user defined models can be together to organize much more complex and large model.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권12호
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• pp.547-552
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• 2014

플리커, 페이스북과 같은 대용량 소셜 미디어 공유 사이트의 발전으로 이미지 정보가 매우 빠르게 증가하고 있다. 이에 따라 소셜 이미지를 정확하게 검색하기 위한 다양한 연구가 활발히 진행되고 있다. 이미지 태그들의 의미적 연관성을 이용하여 태그기반의 이미지 검색의 정확도를 높이고자 하는 연구를 비롯하여 이미지 단어집(Bag of Visual Words)을 기반으로 웹 이미지를 분류하는 연구도 다양하게 진행되고 있다. 본 논문에서는 이미지에서 배경과 같은 중요도가 떨어지는 정보를 제거하여 중요부분을 찾는 GBVS(Graph Based Visual Saliency)모델을 기존 연구에 사용할 것을 제안한다. 제안하는 방법은 첫 번째, 이미지 태그들의 의미적 연관성을 이용해 1차 분류된 데이터베이스에 SIFT알고리즘을 사용하여 이미지 단어집(BoVW)을 만든다. 두 번째, 테스트할 이미지에 GBVS를 통해서 이미지의 관심영역을 선택하여 테스트한다. 의미연관성 태그와 SIFT기반의 이미지 단어집을 사용한 기존의 방법에 GBVS를 적용한 결과 더 높은 정확도를 보임을 확인하였다.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• 영재교육연구
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• 제20권1호
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• pp.1-30
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• 2010

본고는 미술영재성 판별에 따른 인지적 능력과 관련하여 문헌연구와 선행연구들을 바탕으로 미술영재성과 인지능력과의 관계를 고찰함으로써 초등학교 아동의 미술영재성 판별에 따른 인지능력검사모형을 구안하고자 하는 데 있다. 이러한 연구목적을 달성하기 위해 먼저, 미술영재성과 인지능력의 관계를 고찰하여 미술영재성의 구성요인으로서 인지능력의 타당성을 규정한 다음, 앞선 문헌연구를 통해 초등학교 아동의 미술영재성 판별에 따른 인지능력검사모형을 구안하였다. 그리고 구안된 검사모형의 타당성과 신뢰성을 검증하기 위해 일반학급 아동집단과 미술영재 아동집단을 대상으로 검사를 실시하였다. 그 결과 초등학교 아동의 미술영재성 판별에 따른 인지능력의 구성요인으로서 시각적 사고력과 공간 지각력, 비판적 사고력이 논리적, 경험적으로 타당성이 있다고 검증되었다. 이러한 연구의 결과는 앞으로 이루어질 초등학교 아동의 미술영재성 판별에 대한 다양한 모색의 가능성과 미술영재교육 프로그램의 개발에 새로운 접근을 제공해줄 수 있을 것이다.

• 한국CDE학회논문집
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• 제15권2호
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• pp.136-143
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• 2010

Realistic Modeling is to maximize the reality of the environment in which perception is made by virtual environment or remote control using two or more senses of human. Especially, the field of haptic rendering, which provides reality through interaction of visual and tactual sense in realistic model, has brought attention. Haptic rendering calculates the force caused by model deformation during interaction with a virtual model and returns it to the user. Deformable model in the haptic rendering has more complexity than a rigid body because the deformation is calculated inside as well as the outside the model. For this model, Gibson suggested the 3D ChainMail algorithm using volumetric data. However, in case of the deformable model with non-homogeneous materials, there were some discordances between visual and tactual sense information when calculating the force-feedback in real time. Therefore, we propose an algorithm for the Volume Haptic Rendering of non-homogeneous deformable object that reflects the force-feedback consistently in real time, depending on visual information (the amount of deformation), without any post-processing.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1386-1394
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• 2022

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

• Journal of Mechanical Science and Technology
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• 제14권7호
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• pp.782-788
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• 2000

In this paper, we present a new approach to visual feedback control using image-based visual servoing with stereo vision. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only around a desired location but also at other locations. The suggested technique can guide a robot manipulator to the desired location without providing a priori knowledge such as the relative distance to the desired location or the model of an object even when the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by experimental results and compared with conventional control methods for an assembly robot.

• 한국통신학회논문지
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• 제23권9A호
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• pp.2313-2324
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• 1998

Although visual programming is used in many fields of computer science and engineering, some dis-advantages can be found when they work together in an integrated programming environment. To overcome these shortcomings, there have been researches in combining multiparadigm with visual programming. However they have failed because they tried to combine the paramdigms without any coceptural model and structured method. In this paper, we investigate a new multiparadigm visual programming environment (MVPE), in which dataflow paradigm, form-based paradign, direct manipulation paradigm, and object-oriented paradigm are integrated together in an object-oriented way, based on the conceptual model of "method = paradigm, " This MVPE would overcome the limits of visual programming, and may also lead to the new discipline of visual programming environment.vironment.

• 센서학회지
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• 제33권2호
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• pp.78-85
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• 2024

We proposed a method for visual place recognition that represents images using objects as visual words. Visual words represent the various objects present in urban environments. To detect various objects within the images, we implemented and used a zero-shot detector based on a large-scale image language model. This zero-shot detector enables the detection of various objects in urban environments without additional training. In the process of creating histograms using the proposed method, frequency-based weighting was applied to consider the importance of each object. Through experiments with open datasets, the potential of the proposed method was demonstrated by comparing it with another method, even in situations involving environmental or viewpoint changes.