• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.7-16
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• 2002

The Post-clustering algorithms, which cluster the results of Web search engine, have several different requirements from conventional clustering algorithms. In this paper, we propose the new post-clustering algorithm satisfying those requirements as many as possible. The proposed Concept ART is the form of combining the concept vector that have several advantages in document clustering with Fuzzy ART known as real-time clustering algorithms. Moreover we show that it is applicable to general-purpose clustering as well as post-clustering

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.85-96
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• 1999

In a number of predictive video compression standards, the motion is compensated by the block-based motion compensation (BMC). The effective motion field used for the prediction by the BMC is obviously discontinuous since one motion vector is used for the entire macro-block. The usage of discontinuous motion field for the prediction causes the blocky artifacts and one obvious approach for eliminating such artifacts is to use a smoothed motion field. The optimal procedure will depend on the type of motion within the video. In this paper, several procedures for the motion vectors are considered. For any interpolation or approaches, however, the motion vectors as provided by the block matching algorithm(BMA) are no longer optimal. The optimum motion vectors(still one per macro-block) must minimize the of the displaced frame difference (DFD). We propose a unified algorithm that computes the optimum motion vectors to minimize the of the DFD using a conjugate gradient search. The proposed algorithm has been implemented and tested for the affine transformation based motion compensation (ATMC), the bilinear transformation based motion compensation (BTMC) and our own filtered motion compensation(FMC). The performance of these different approaches will be compared against the BMC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.121-127
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• 2009

The Multistage Feature-based Classification Model(MFCM) is proposed in this paper. MFCM does not use whole feature vectors extracted from the original data at once to classify each data, but use only groups related to each feature vector to classify separately. In the training stage, the contribution rate calculated from each feature vector group is drew throughout the accuracy of each feature vector group and then, in the testing stage, the final classification result is obtained by applying weights corresponding to the contribution rate of each feature vector group. In this paper, the proposed MFCM algorithm is applied to the problem of music genre classification. The results demonstrate that the proposed MFCM outperforms conventional algorithms by 7% - 13% on average in terms of classification accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.487-492
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• 2011

In this paper, we proposed a new design methodology to improve the classification performance of the Nearest Prototype Classifier which is one of the simplest classification algorithm. To optimize the position vectors of the prototypes in the nearest prototype classifier, we use the differential evolutionary algorithm. The optimized position vectors of the prototypes result in the improvement of the classification performance. The new method to determine the class labels of the prototypes, which are defined by the differential evolutionary algorithm, is proposed. In addition, the experimental application covers a comparative analysis including several previously commonly encountered methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.35-38
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• 2013

최근, 대용량 영상 데이터베이스가 축적되면서 영상 인식과 영상 검색 분야가 주목받고 있으며, 다양한 디바이스에 따라 생성되는 영상의 해상도가 상이하게 나타나고 있다. 본 논문에서는 내용-기반 영상 검색을 위한 새로운 칼라 기술자를 제안한다. 제안 알고리즘에서는 공간 칼라 정보에 대한 웨이블릿 변환과 채널 및 변환 서브밴드에 따른 가중치를 적용하여 칼라 특징 벡터를 추출한다. 시뮬레이션을 통하여 제안하는 알고리즘의 검색 성능을 평가하였으며, 유사한 특징 벡터 크기를 기준으로, 기존의 MPEG-7 등의 칼라 검색 기술자보다 다중-해상도의 영상 데이터베이스에서 향상된 검색율을 보임을 확인하였다. 본 논문에서 제시한 알고리즘은 단일 특성의 특징 벡터를 추출하는 검색 기술자로써, 다중 특징으로 결합하기 위한 기본 기술자로 활용될 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.146-150
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• 1998

In this paper, we propose a nonlinear system identification method using the genetic algorithm. We represent the nonlinear system as a parameter vector and a measurement vector of ARMAX model. In order to identify the nonlinear system, we find the parameter vector using the genetic algorithm. The parameter vector is regarded as a chromosome of gene. The error between the desired output and estimated output every sampling period is used to calculate the fitness of one gene. The simulation results showed the effectiveness of using the genetic algorithm in the nonlinear system identification.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.675-678
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• 1999

본 논문에서는 음소별 코드북 개수의 선택과 벡터 양자화에 따른 음소 인식률과 고립단어 인식률에 대하여 다룬다. 음성모델은 이산 확률 밀도를 갖는 DHMM(Discrete Hidden Markov Model)을 사용하였으며, 코드북 생성과 벡터 양자화 알고리즘으로는 K-means 알고리즘과 LBG(Linde, Buzo, Gray) 알고리즘을 사용하였다 음소별 코드북 개수와 벡터 양자화를 최적화함으로써 음소 인식률을 향상시킬 수 있으며, 그 결과 안정된 고립단어 인식률을 얻을 수 있다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.966-967
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• 2008

2kW급 선형 압축기용 액츄에이터로 직선 왕복 운동을 동작하게 하기 위하여 2상 영구자석형 횡자속 선형 전동기(Permanent Magnet Transverse Flux Linear Machine; PM-TFLM)와 스프링을 조합하여 선형 공진 시스템을 구성하였다. 선형전동기의 이동자를 공진점부근에서 왕복 운동을 하기 위해서 빠른 왕복 운전과 적절한 운전 알고리즘이 필요하게 된다. 먼저 2상으로 이루어진 PM-TFLM의 순시 토오크 제어를 위하여 벡터 제어 알고리즘을 설계하여 구현하고 피스톤, 스피링 및 부하에 따라 운전제어를 수행하는 방법에 대하여 연구를 하였다. 종래의 3상 교류 전동기의 순시 토오크 제어에 적용하는 벡터제어 알고리즘을 2상 PM-TFLM에 적용하여 그 타당성을 보이고 빠른 왕복운전을 안정적으로 수행함을 실험을 통하여 입증하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.55-56
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• 2018

화력발전소의 중요 구성품인 보일러 튜브의 예기치 못한 누설 사고로 인해 수억원에 해당하는 손실이 발생하고 있다. 본 논문에서는 보일러 튜브의 누설 감지를 위해 유전 알고리즘을 이용하여 추출 가능한 특징들 중 누수 감지에 유용한 특징들을 선택하고, 선택된 특징으로 서포트 벡터 머신을 이용하여 보일러 튜브의 누설 감지하는 방법을 제안한다. 이는 뛰어난 성능을 보였으며, 향후 본 기술을 이용하면 발전소의 손실 예방에 크게 도움이 될 것으로 기대된다.