• 제목/요약/키워드: Correlation Map

검색결과 519건 처리시간 0.028초

장애물 추정 및 클러스터링을 위한 장애물 데이터베이스 관리 모듈 개발: G-eye 관리 시스템 (Development of Obstacle Database Management Module for Obstacle Estimation and Clustering: G-eye Management System)

  • 민성희;오유수
    • 한국멀티미디어학회논문지
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    • 제20권2호
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    • pp.344-351
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    • 2017
  • In this paper, we propose the obstacle database management module for obstacle estimation and clustering. The proposed G-eye manager system can create customized walking route for blind people using the UI manager and verify the coordinates of the path. Especially, G-eye management system designed a regional information module. The regional information module can improve the loading speed of the obstacle data by classifying the local information by clustering the coordinates of the obstacle. In this paper, we evaluate the reliability of the walking route generated from the obstacle map. We obtain the coordinate value of the path avoiding the virtual obstacle from the proposed system and analyze the error rate of the path avoiding the obstacle according to the size of the obstacle. And we analyze the correlation between obstacle size and route by classifying virtual obstacles into sizes.

컨벌루션 특징맵과 코릴레이션 필터를 이용한 물체 추적에 관한 연구 (A Study on Object Tracking using Convolution Feature Map and Correlation Filter)

  • 임수창;김도연
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2016년도 추계학술발표대회
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    • pp.661-662
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    • 2016
  • 컴퓨터비전의 한 분야인 추적은 다양한 방법론들에 근거하여 활발히 연구되어온 분야이다. 추적알고리즘은 연속되는 영상 시퀀스의 객체를 지속적으로 추적하는 방법으로, 객체의 외형 변형, 이동, 회전, 폐색등 복잡한 환경에서도 강건히 추적하는 것에 초점이 맞춰져 있다. 본 논문에서는 딥러닝의 한 부류인 CNN의 컨볼루션 레이어에서 출력되는 특징맵과 변화되는 객체에 적응적으로 대응하는 코릴레이션 필터를 결합하여 복잡한 환경에서도 객체를 추적하는 방법을 제안한다.

굴삭기 장애물 인식 및 접촉방지 시스템에 관한 연구 (A Study on an Obstacle Recognition and Contact Protection System for Excavator)

  • 김성호;천종현;박경섭;임종형
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.398-398
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    • 2000
  • Since there is a blind zone in driver's view around the excavator, industrial accidents between the equipment and the workers within the zone have been occurred frequently. The purpose of this paper is to develop a obstacle recognition system which can prevent such an accident by providing the driver with the information on direction and distance of the obstacle within the blind zone. We designed the ultrasonic sensor based obstacle recognition system which consists of sensor arrays and a control unit connected via CAN(controller area network). The Cross-correlation technique and histogramic probability distribution method are used as a reliable obstacle detection algorithms to remove the environmental noise. The experimental results using a real excavator show the effectiveness of the system.

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Determination of Sampling Unit Size for Cultivation Area Survey using Remote Sensing Technology

  • Park, Jin-Woo;Shin, Gi-Eun;Lee, Suk-Hoon;Byun, Jong-Seok
    • 응용통계연구
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    • 제25권5호
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    • pp.733-741
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    • 2012
  • The successful launch of Arirang satellites allow the acquisition of high resolution satellite imagery of Korean territory and enables the transition from the conventional cultivation area survey method to new image based methods adopted in advanced nations. In this study, we suggested reasonable sizes of the primary sampling unit and the secondary sampling unit for the satellite imagery based sampling design in 8 provinces preselected for this research. The PSU size was determined mainly in consideration of intracorrelation that shows the degree of homogeneity within each cluster and the efficiency of the image process. For the SSU size, we considered the relative standard error and the differences between the land cover maps produced by the Ministry of Environment and the satellite imagery processed by the National Statistical Office.

A Study on Risk Evaluation of Crime in the Seoul Metropolitan Area based on Poisson Regression Model

  • Kim, Hag-Yeol;Yu, Hye-Kyung;Park, Man-Sik;Heo, Tae-Young
    • 응용통계연구
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    • 제25권5호
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    • pp.865-875
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    • 2012
  • In this study, we identify the variables that affect the number of crime and spatial correlation in the Seoul metropolitan area, in addition, we measure the relative risk on the incidence of crime by a Poisson regression model. We suggest a statistical methodology to make a risk map for crime based on relative risk instead of the total event of crime by region using the Geographic Information System. To demonstrate the use and advantages of this methodology, this study presents an analyses of the total crime count in 25 wards in the Seoul metropolitan area.

Phase vector sum을 이용한 디젤엔진 구조진동의 평가 (Evaluation of Diesel Engine Structural Vibration Using Phase Vector Sum)

  • 이수목;김관영
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 추계학술대회논문집
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    • pp.383-388
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    • 2003
  • As an effective way of response evaluation in structural vibration analysis, the phase vector sum(PVS) method used in shaft torsional vibration analysis is introduced. Basic relation of PVS applicable to structural problem is derived and applied to Diesel engine structures. Concepts of forced phase vector sum (FPVS) and significance level (SL) are proposed to visualize the correlation between excitation orders and vibration modes in the SL map. The maximum responses and SL are compared and reviewed to confirm the validity of the method. It is regarded FPVS is adequate to newly evaluate the structural vibration based on excitation information.

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Modeling Aided Lead Design of FAK Inhibitors

  • Madhavan, Thirumurthy
    • 통합자연과학논문집
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    • 제4권4호
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    • pp.266-272
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    • 2011
  • Focal adhesion kinase (FAK) is a potential target for the treatment of primary cancers as well as prevention of tumor metastasis. To understand the structural and chemical features of FAK inhibitors, we report comparative molecular field analysis (CoMFA) for the series of 7H-pyrrolo(2,3-d)pyrimidines. The CoMFA models showed good correlation between the actual and predicted values for training set molecules. Our results indicated the ligand-based alignment has produced better statistical results for CoMFA ($q^2$ = 0.505, $r^2$ = 0.950). Both models were validated using test set compounds, and gave good predictive values of 0.537. The statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The contour map from 3D-QSAR models explains nicely the structure-activity relationships of FAK inhibitors and our results would give proper guidelines to further enhance the activity of novel inhibitors.

선형구조 혼돈계를 이용한 이미지 암호와 방법 연구 (Research on the Image Encryption Method using a Linear-structure Chaos System)

  • 조창호;임거수
    • 디지털산업정보학회논문지
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    • 제7권4호
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    • pp.75-79
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    • 2011
  • With the rapid growth of digital communication and the internet, the importance of conducting research on data encryption methods is increasing. Some of the pertinent researches that have been conducted so far introduced data encryption methods using chaos systems, and numerous researches are currently being conducted on such methods. The signals produced by the chaos systems are called "determined noise," and if this is applied to data encryption, very effective results can be obtained. Using the Henon map, the relationship between the non-linearity of the chaos system and the strength of encryption was analyzed, and a linear-structure chaos system that uses non-linearity as a variable for encryption strength was constructed. Using the constructed chaos system, an image was encrypted and decoded, and the correlation coefficient of the linear-structure chaos system's performance was calculated and then analyzed.

시간 지연을 갖는 쌍전파 신경회로망을 이용한 근전도 신호인식에 관한 연구 (A Study on EMG Signals Recognition using Time Delayed Counterpropagation Neural Network)

  • 권장우;정인길;홍승홍
    • 대한의용생체공학회:의공학회지
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    • 제17권3호
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    • pp.395-401
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    • 1996
  • In this paper a new neural network model, time delayed counterpropagation neural networks (TDCPN) which have high recognition rate and short total learning time, is proposed for electromyogram(EMG) recognition. Signals the proposed model increases the recognition rates after learned the regional temporal correlation of patterns using time delay properties in input layer, and decreases the learning time by using winner-takes-all learning rule. The ouotar learning rule is put at the output layer so that the input pattern is able to map a desired output. We test the performance of this model with EMG signals collected from a normal subject. Experimental results show that the recognition rates of the suggested model is better and the learning time is shorter than those of TDNN and CPN.

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Wavelet Transform based Image Registration using MCDT Method for Multi-Image

  • Lee, Choel;Lee, Jungsuk;Jung, Kyedong;Lee, Jong-Yong
    • International Journal of Internet, Broadcasting and Communication
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    • 제7권1호
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    • pp.36-41
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    • 2015
  • This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.