• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.89-93
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• 2009

Embedded systems are becoming more popular as many embedded platforms have become more affordable. It offers a compact solution for many different problems including computer vision applications. Texture classification can be used to solve various problems, and implementing it in embedded platforms will help in deploying these applications into the market. This paper proposes to deploy the texture classification algorithms onto the embedded computer vision (ECV) platform. Two algorithms are compared; grey level co-occurrence matrices (GLCM) and Gabor filters. Experimental results show that raw GLCM on MATLAB could achieves 50ms, being the fastest algorithm on the PC platform. Classification speed achieved on PC and ECV platform, in C, is 43ms and 3708ms respectively. Raw GLCM could achieve only 90.86% accuracy compared to the combination feature (GLCM and Gabor filters) at 91.06% accuracy. Overall, evaluating all results in terms of classification speed and accuracy, raw GLCM is more suitable to be implemented onto the ECV platform.

• 대한두경부종양학회지
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• 제4권1호
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• pp.5-11
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• 1988

CT examination has been used in the preoperative examination of patients with head and neck cancer. The accuracy of CT in detecting nodal metastases has not been well established. We studied 35 patients (41 neck specimens) with head and neck cancer who underwent neck dissection. Surgical pathologic findings were compared with preoperative CT scan to establish the diagnostic accuracy for cervical lymph node metastases. The results of physical examination, CT scans of neck and histologic examinations were compared each other. The overall diagnostic accuracy of CT was 83.3%. Comparison with clinical accuracy shows the CT scan to be superior to the clinical examination in spite of careful physical examination, particularly in detecting occult metastases.

• 대한공간정보학회지
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• 제8권2호
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• pp.23-33
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• 2000

본 연구에서는 인공위성영상을 이용한 토지피복 분류방법 중 파라메트릭한 분류와 비-파라메트릭한 분류의 대표성을 띤 최대우도 분류법과 신경망을 이용한 분류방법을 사용하여 분류정확도를 비교하였다. 분류정확도의 평가에 있어서 일반적인 분석가들이 사용하는 훈련지역에 대한 분류정확도의 분석뿐만 아니라, 시험지역에 대한 정확도분석을 하였다. 그 결과, 최대우도분류기에 비하여 신경망의 분류기가 일반적인 훈련데이터의 분류에 있어서 약 3% 우월하였으며, 지상검증데이터를 사용한 분류결과에서는 시험에 사용된 두 분류기 모두 빈약한 분류결과를 나타내었으나, 신경망에 의한 분류가 최대우도에 비하여 약 10%정도 보다 신뢰할 수 있는 결과를 얻을 수 있었다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 춘계학술대회 논문집
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• pp.183-187
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• 1996

On the machine measuring system composed of touch trigger probes, a DNC module, a CMM module, an analysis module and a man-machine interface unit was developed. Measuring accuracy is affected by working accuracy of the on the machine measuring system. The working accuracy of the system is due to geometric errors of th machine tool, servo errors of feed drives and positioning errors of probes. In order to compensate for the measuring errors due to the working accuracy, a calibration module was developed. The measuring automation system was realized with the on the machine measuring system and an IBM-PC on the machine center through a RS-232C. It turns the machining machine (CMM). The system is used for dimensional checking of machined components. initial job setup, part identification, identification of machining errors due to deflection and wear of tools. cutter run out, and calibration of machine tools. A horizontal machining center equipped with FANUC OMC wre used for verification of the system. The validity and reliability of the system. The validity and reliability of the system were confirmed through a series of experiments with gage blocks, ring gages, comparison measurement with a commercial CMM, and so on.

• 대한기계학회논문집A
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• 제31권4호
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• pp.490-495
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• 2007

This research aims to examine accuracy and efficiency of the first four moments corresponding to mean, standard deviation, skewness, and kurtosis, which are estimated by a function approximation moment method (FAMM). In FAMM, the moments are estimated from an approximating quadratic function of a system response function. The function approximation is performed on a specially selected experimental region for accuracy, and the number of function evaluations is taken equal to that of the unknown coefficients for efficiency. For this purpose, three error-minimizing conditions are utilized and corresponding canonical experimental regions constructed accordingly. An interpolation function is then obtained using a D-optimal design and then the first four moments of it are obtained as the estimates for the system response function. In order to verify accuracy and efficiency of FAMM, several non-linear examples are considered including a polynomial of order 4, an exponential function, and a rational function. The moments calculated from various coefficients of variation show very good accuracy and efficiency in comparison with those from analytic integration or the Monte Carlo simulation and the experimental design technique proposed by Taguchi and updated by D'Errico and Zaino.

• 한국컴퓨터정보학회논문지
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• 제18권1호
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• pp.177-183
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• 2013

본 논문에서는 데이터 마이닝에서 분류 작업을 실시할 때 그 분류정확도을 측정하기 위해 Cohen의 kappa 계수와 weighted kappa 계수를 제안하였다. kappa 계수는 우연에 의해 생기는 분류를 보정하여 분류정확도을 측정하며 명목척도와 순서척도의 데이터에 대해 사용된다. 특히 순서척도의 데이터에서는 오분류의 크기를 가중치에 의해 정량화하여 분류정확도을 측정하는 weighted kappa 계수가 더 유용하게 사용된다. weighted kappa 계수 계산을 위해서는 2가지 가중치(일차형 가중치, 이차형 가중치)를 사용하였다.. 또한 실제 데이터인 지방간 데이터에 대해 kappa 계수와 weighted kappa 계수를 계산하여 비교하였다.

• 한국측량학회지
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• 제17권3호
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• pp.283-292
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• 1999

본 논문에서는 대축척 항공 사진(1/5,000)을 촬영할 때 수신한 GPS 자료를 처리하여 결정한 항공 사진 카메라의 투영중심 위치를 이용한 항공삼각측량에 대해서 연구하였다. 항공삼각측량에 적용 가능성을 검토하기 위해 GPS자료를 처리하여 모델 조정법으로 결정한 투영중심의 위치와 비교하여 정확도 및 오차를 분석하였다. 또한, GPS 자료로 결정한 투영중심의 위치를 광속 조정법에 적용하였다. 기준국으로부터 30 km이내인 경우 L1 반송파 자료를 이용하여 결정한 투영중심 위치의 정확도는 일정하고, 4개의 기준점으로 평면(XY) 정확도(RMS)는 13 cm, 높이(Z) 정확도(RMS)는 15 cm로 수치지도 제작에 필요한 정확도를 얻을 수 있었다. 따라서, GPS를 항공삼각측량에 이용함으로써 경제적인 지도 제작 방안을 제시하였다.

• 대한원격탐사학회지
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• 제35권1호
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• pp.83-92
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• 2019

Land cover (LC) is an important factor in socioeconomic and environmental studies. According to various studies, a number of LC maps, including global land cover (GLC) datasets, are made using polar orbit satellite data. Due to the insufficiencies of reference datasets in Northeast Asia, several LC maps display discrepancies in that region. In this paper, we performed a feasibility assessment of LC mapping using Geostationary Ocean Color Imager (GOCI) data over Northeast Asia. To produce the LC map, the GOCI normalized difference vegetation index (NDVI) was used as an input dataset and a level-2 LC map of South Korea was used as a reference dataset to evaluate the LC map. In this paper, 7 LC types(urban, croplands, forest, grasslands, wetlands, barren, and water) were defined to reflect Northeast Asian LC. The LC map was produced via principal component analysis (PCA) with K-means clustering, and a sensitivity analysis was performed. The overall accuracy was calculated to be 77.94%. Furthermore, to assess the accuracy of the LC map not only in South Korea but also in Northeast Asia, 6 GLC datasets (IGBP, UMD, GLC2000, GlobCover2009, MCD12Q1, GlobeLand30) were used as comparison datasets. The accuracy scores for the 6 GLC datasets were calculated to be 59.41%, 56.82%, 60.97%, 51.71%, 70.24%, and 72.80%, respectively. Therefore, the first attempt to produce the LC map using geostationary satellite data is considered to be acceptable.

• 한국인공지능학회지
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• 제11권1호
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• pp.1-7
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• 2023

In this paper, a study was conducted to compare the prediction model of cardiovascular disease occurrence. It is the No.1 disease that accounts for 1/3 of the world's causes of death, and it is also the No. 2 cause of death in Korea. Primary prevention is the most important factor in preventing cardiovascular diseases before they occur. Early diagnosis and treatment are also more important, as they play a role in reducing mortality and morbidity. The Results of an experiment using Azure ML, Logistic Regression showed 88.6% accuracy, Decision Tree showed 86.4% accuracy, and Support Vector Machine (SVM) showed 83.7% accuracy. In addition to the accuracy of the ROC curve, AUC is 94.5%, 93%, and 92.4%, indicating that the performance of the machine learning algorithm model is suitable, and among them, the results of applying the logistic regression algorithm model are the most accurate. Through this paper, visualization by comparing the algorithms can serve as an objective assistant for diagnosis and guide the direction of diagnosis made by doctors in the actual medical field.

• 예술인문사회 융합 멀티미디어 논문지
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• 제7권8호
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• pp.305-314
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• 2017

Clustering is a method that collects data objects into groups based on their similary. Performance of the state-of-the-art clustering methods is different according to the data characteristics. There have been numerous studies that performed experiments to compare the accuracy of the state-of-the-art clustering methods by applying various kinds of datasets. A common problem of these studies is that they only consider clustering algorithms that yield the most accurate results for a particular dataset. They do not consider what factors affect the execution time of each clustering method and how they are affected. Nevertheless, execution time is an important factor in clustering performance if there is no significant difference in accuracy. In order to solve the problems of the existing research, through a series of experiments using various types of datasets, we compare the accuracy of four representative clustering methods. In addition, we perform practical clustering performance comparisons by deriving time complexity and identifying factors that influences to its performance.