• 지능정보연구
• /
• 제15권2호
• /
• pp.1-13
• /
• 2009

개념 기반 이미지풍경 분류 기법은 데이터베이스에 있는 대량의 이미지 를 카테고리별로 구분하는 많이 적용되는 응용분야이다. 풍경이 속하는 카테고리를 알면 데이터베이스에서 해변, 산, 숲, 필드와 같은 필요한 풍경사진을 찾고자 할 때 불필요한 이미지를 필터링하여 신속하고 정확하게 찾을 수 있다. 본 논문에서는 이미지 분류를 위한 시멘틱 모델링 기반의 적응 세그멘테이션 기법을 제안 한다. 잔디, 물, 하늘과 같은 시멘틱 개념에 따른 이미지를 서브구역으로 나누어 세그멘테이션을 한다. 세그멘테이션은 에지탐색을 이용하고 또한 K-Nearest(K-NN)를 이용하여 세그멘테이션을 한다. 세그멘테이션 과정에서 이미지의 복잡도에 따라 적응적으로 서브구역으로 나눈다. 실험에서는 Vosel과 schiele가 제안한 방법과의 비교를 통해서 정확도면에서 제안된 연구의 우수성을 보여준다.

• 제어로봇시스템학회논문지
• /
• 제10권7호
• /
• pp.611-617
• /
• 2004

This paper presents a simple method of rotational motion estimation and correction for roll axis stabilization of an image. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. Roll motion correction is then performed by the nearest neighbor interpolation technique. To show the effectiveness of our approach, the synthetic and real images are evaluated, resulting in better performance than the previous ones.

• 산업공학
• /
• 제7권2호
• /
• pp.87-97
• /
• 1994

Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involves such complicated and stochastic conditions as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method of the current system in terms of total logistics cost and driving time. This heuristics algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(A)
• /
• pp.65-68
• /
• 2011

최근 무선 통신 기술의 발달 및 모바일 기기의 발달로 인하여 위치 기반 서비스가 주목을 받고 있다. 그러나 사용자의 정확한 위치정보를 통해 LBS 서버에 질의를 요청하는 것은 심각한 개인 정보 누출의 위협이 될 수 있기 때문에, 사용자 정보 보호를 위해 도로 네트워크를 고려하여 질의영역을 생성하는 연구가 활발히 진행되어 왔다. 따라서 질의영역에 대한 효율적인 질의 처리 방법이 요구된다. 이를 위해, 본 논문에서는 도로 네트워크에서 사용자 정보 보호를 지원하는 질의영역에 대한 k최근접점 질의 처리 알고리즘을 제안한다. 제안하는 기법은 POI를 효율적으로 검색하기 위하여 Island 인덱스를 사용한다. 또한, 본 논문은 질의 처리 성능을 향상시키기 위해 적응적 Island 인덱스를 생성하는 방법을 제안한다. 마지막으로, 성능평가를 통해 제안하는 기법이 기존 기법들에 비해 네트워크 확장 비용 및 서비스 시간 측면에서 우수함을 보인다.

• 로봇학회논문지
• /
• 제4권4호
• /
• pp.305-311
• /
• 2009

FastSLAM is a factored solution to SLAM problem using a Rao-Blackwellized particle filter. In this paper, we propose a practical FastSLAM implementation method using an infrared camera for indoor environments. The infrared camera is equipped on a Pioneer3 robot and looks upward direction to the ceiling which has infrared tags with the same height. The infrared tags are detected with theinfrared camera as measurements, and the Nearest Neighbor method is used to solve the unknown data association problem. The global map is successfully built and the robot pose is predicted in real time by the FastSLAM2.0 algorithm. The experiment result shows the accuracy and robustness of the proposed method in practical indoor environment.

• Journal of Information Processing Systems
• /
• 제3권2호
• /
• pp.73-81
• /
• 2007

In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naive Bayesian classification algorithms. The architecture of our system is simple and modularized in that each sub-module of the system could be changed or improved efficiently. Moreover, it provides various feature selection mechanisms to be applied to optimize the general-purpose classifiers for a specific domain. As for the enhanced classification performance, our system provides conditional probability boosting (CPB) mechanism which could be used in various domains. In the mood classification domain, our optimized framework using the CPB algorithm showed 1% of improvement in precision and 2% in recall compared with the baseline.

• 한국컴퓨터정보학회논문지
• /
• 제21권10호
• /
• pp.55-62
• /
• 2016

In this paper, we present indoor localization technologies using the bluetooth signal categorizing them into proximity based, triangulation based and fingerprinting based technologies. Then we provide localization accuracy improvement algorithms such as moving average, K-means, particle filter, and K-Nearest neighbor algorithms. We define important performance issues for indoor localization technologies and analyze recent technologies according to the performance issues. Finally we provide experimental results for correlation between RSSI and distance. We believe that this paper provide wise view and necessary information for recent localization technologies using the bluetooth signal.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제12권1호
• /
• pp.1-5
• /
• 2012

Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been published for dimension reduction. Also, data augmentation is another approach to analyze data efficiently. Support vector machine (SVM) algorithm is a representative technique for dimension augmentation. The SVM maps original data to a feature space with high dimension to get the optimal decision plane. Both data reduction and augmentation have been used to solve diverse problems in data analysis. In this paper, we compare the strengths and weaknesses of dimension reduction and augmentation for classification and propose a classification method using data reduction for classification. We will carry out experiments for comparative studies to verify the performance of this research.

• Asia pacific journal of information systems
• /
• 제12권2호
• /
• pp.179-195
• /
• 2002

In this research, we developed an efficient Hangul document classification system for text mining. We mean 'efficient' by maintaining an acceptable classification performance while taking shorter computing time. In our system, given a query document, k documents are first retrieved from the document case base using the k-nearest neighbor technique, which is the main algorithm of case-based reasoning. Then, TFIDF method, which is the traditional vector model in information retrieval technique, is applied to the query document and the k retrieved documents to classify the query document. We call this procedure 'CB_TFIDF' method. The result of our research showed that the classification accuracy of CB_TFIDF was similar to that of traditional TFIDF method. However, the average time for classifying one document decreased remarkably.

• 한국전자거래학회:학술대회논문집
• /
• 한국전자거래학회 2005년도 e-Biz World Conference 2005
• /
• pp.189-194
• /
• 2005

Many studies have been conducted to classify documents, and to extract useful information from documents. However, most search engines have used a keyword based method. This method does not search and classify documents effectively. This paper identifies structures of XML document based on the fact that the XML document has a structural document using a set theory, which is suggested by Broder, and attempts a test for clustering XML document by applying a k-nearest neighbor algorithm. In addition, this study investigates the effectiveness of the clustering technique for large scaled data, compared to the existing bitmap method, by applying a test, which reveals a difference between the clause based documents instead of using a type of vector, in order to measure the similarity between the existing methods.