• 한국정보통신학회논문지
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• 제23권12호
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• pp.1500-1505
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• 2019

현재 전 세계적으로 ICT 스마트시티의 일환으로 도시교통 문제해결을 위한 차세대 지능형 교통시스템인 C-ITS(Cooperative-Intelligent Transport Systems) 구축을 추진하고 있다. C-ITS와 함께 자율주행 서비스를 실현하기 위해서는 첨단 도로 인프라의 역할이 중요하다. 그리고 중장기적인 C-ITS, 자율주행서비스의 연구와 함께 단기적으로 도로 교통안전을 위한 보다 현실적인 솔루션 제시가 필요하다. 따라서 본 논문에서는 IoT 가드 레일을 기반으로 C-ITS의 필수 요구정보인 교통흐름과 사고위험 정보를 감지·분석하여, 도로 현장에 즉각적인 경보와 원격 모니터링을 제공할 수 있는 고속도로 사고감지 및 경보 시스템을 제안한다. 지능형 IoT 가드 레일은 장기적으로 C-ITS와 자율주행 서비스에서 요구하는 실제 도로 현장에서의 데이터를 제공하는 지능적 첨단 도로 인프라로서 활용될 것으로 기대된다.

• Journal of information and communication convergence engineering
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• 제11권3호
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• pp.207-215
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• 2013

In this paper, we address the challenging computer vision problem of obtaining a reliable facial expression analysis from a naturally interacting person. We propose a system that combines a 3D generic face model, 3D head tracking, and 2D tracker to track facial landmarks and recognize expressions. First, we extract facial landmarks from a neutral frontal face, and then we deform a 3D generic face to fit the input face. Next, we use our real-time 3D head tracking module to track a person's head in 3D and predict facial landmark positions in 2D using the projection from the updated 3D face model. Finally, we use tracked 2D landmarks to update the 3D landmarks. This integrated tracking loop enables efficient tracking of the non-rigid parts of a face in the presence of large 3D head motion. We conducted experiments for facial expression recognition using both framebased and sequence-based approaches. Our method provides a 75.9% recognition rate in 8 subjects with 7 key expressions. Our approach provides a considerable step forward toward new applications including human-computer interactions, behavioral science, robotics, and game applications.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.105-109
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• 2006

In this paper, we constructed a two-phase spam-mail filtering system based on the lexical and conceptual information. There are two kinds of information that can distinguish the spam mail from the ham (non-spam) mail. The definite information is the mail sender's information, URL, a certain spam keyword list, and the less definite information is the word list and concept codes extracted from the mail body. We first classified the spam mail by using the definite information, and then used the less definite information. We used the lexical information and concept codes contained in the email body for SVM learning in the 2nd phase. According to our results the ham misclassification rate was reduced if more lexical information was used as features, and the spam misclassification rate was reduced when the concept codes were included in features as well.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.431-434
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• 2003

In this paper we introduce a modified objective function for fuzzy c-means clustering with logistic regression model in the presence of noise cluster. The logistic regression model is commonly used to describe the effect of one or several explanatory variables on a binary response variable. In real application there is very often no sharp boundary between clusters so that fuzzy clustering is often better suited for the data.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.315-317
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• 2003

Neural oscillator is applied in oscillatory systems (Analysis of image information, Voice recognition. Etc...). If we apply established EBPA(Error back Propagation Algorithm) to oscillatory system, we are difficult to presume complicated input's patterns. Therefore, it requires more data at training, and approximation of convergent speed is difficult. In this paper, I studied the neural oscillator as synchronized states with appropriate phase relation between neurons and recognized the Korean alphabet using Neural Oscillator Phase model Synchronization.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.118-121
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• 2003

Human support systems, such as computers and robots, are required to be changed to a machine equipment independently operates and communicate with human, rather than non-sensitivity and obedient machine equipment Therefore, we notice nonverbal language that human recognizes naturally. In addition, we show the validity and constitution of mechanism that recognizes an intention of human using those several information to judge independently.

• 한국지능시스템학회논문지
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• 제2권2호
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• pp.42-60
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• 1992

An adaptive fuzzy system can efficiently classify subimages into four categories according to image activity level for image data compression. The system estimates fuzzy rules by clustering input-output data generated from a given adaptive transform image coding process. The system encodes different images without modification and reduces side information when encoding multiple images. In the second part, a fuzzy system estimates optimal bit maps for the four subimage classes in noisy channels assuming a Gauss-Markov image model. The fuzzy systems respectively estimate the sampled subimage classification and the bit-allocation processes without a mathematical model of how outputs depend on inputs and without rules articulated by experts.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.263-266
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• 2001

It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads and open area without any specific mark such as painted guide line or tape. In this method, Robot navigates with visual sensors, which uses visual information to navigate itself along the road. An Artificial Neural Network System was used to decide where to move. It is designed with USB web camera as visual sensor.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.133-136
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• 2004

This paper proposes a stability condition in affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).

• 한국지능시스템학회논문지
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• 제3권2호
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• pp.36-44
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• 1993

Not all business executives can afford the time or cost of having an expert interpret the output of management science models. They find these models perplexing because they are given in the form of numeric vectors or metrics. In this paper, we discuss the possibility of developing an expert system to assist managers' interpretation of the models' results. Having gained interpreting skills, these executive may integrate the system with commercial software.