• 제목/요약/키워드: 3-Dimensional Network

검색결과 596건 처리시간 0.026초

다중 판별자를 가지는 동적 삼차원 뉴로 시스템 (A Dynamic Three Dimensional Neuro System with Multi-Discriminator)

  • 김성진;이동형;이수동
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권7호
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    • pp.585-594
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    • 2007
  • 오류역전파 방법을 이용하는 신경망들은 패턴들의 학습시간이 매우 오래 걸리고 또한 추가학습과 반복학습의 한계를 가지며, 이런 단점을 보완할 수 있는 이진신경망(Binary Neural Network, BNN)이 Aleksander에 의해 제안되었다. 그러나 BNN도 반복학습에 있어서는 단점을 가지고 있으며, 일반화 패턴을 추출하기 어렵다. 본 논문에서는 BNN의 구조를 개선하여 반복학습과 추가학습이 가능할 뿐 아니라, 특징점들까지 추출할 수 있는 다중 판별자를 가지는 삼차원 뉴로 시스템을 제안한다. 제안된 모델은 기존의 BNN을 기반으로 하여 만들어진 이차원 특징을 가지는 Single Layer Network(SLN)에 귀환회로가 추가되어 특징점들을 누적할 수 있는 삼차원 신경망이다. 학습을 통해 누적된 정보는 판별자의 각 신경세포에 임계치를 조정함으로써 일반화 패턴을 추출할 수 있다. 그리고 생성된 일반화 패턴을 인식에 재사용함으로써 반복학습의 효율성을 높였다. 최종 판정 단계에서는 Maximum Response Detector(MRD)를 이용하였다. 본 논문에서 제안한 시스템을 평가하기 위하여 NIST에서 제공하는 숫자 자료를 이용하였으며, 99.3%의 인식률을 얻었다.

FracSys와 UDEC을 이용한 사면 파괴 양상 분석 통계적 절리망 생성 기법 및 Monte Carlo Simulation을 통한 사면 안정성 해석

  • 김태희;최재원;윤운상;김춘식
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2002년도 봄 학술발표회 논문집
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    • pp.651-656
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    • 2002
  • In general, the most important problem in slope stability analysis is that there is no definite way to describe the natural three-dimensional Joint network. Therefore, the many approaches were tried to anlayze the slope stability. Numerical modeling approach is one of the branch to resolve the complexity of natural system. UDEC, FLAC, and SWEDGE are widely used commercial code for the purpose on stability analysis. For the purpose on the more appropriate application of these kind of code, however, three-dimensional distribution of joint network must be identified in more explicit way. Remaining problem is to definitely describe the three dimensional network of joint and bedding, but it is almost impossible in practical sense. Three dimensional joint generation method with random number generation and the results of generation to UDEC have been applied to settle the refered problems in field site. However, this approach also has a important problem, and it is that joint network is generated only once. This problem lead to the limitation on the application to field case, in practical sense. To get rid of this limitation, Monte Carlo Simulation is proposed in this study 1) statistical analysis of input values and definition of the applied system with statistical parameter, 2) instead of the consideration of generated network as a real system, generated system is just taken as one reliable system, 3) present the design parameters, through the statistical analysis of ouput values Results of this study are not only the probability of failure, but also area of failure block, shear strength, normal strength and failure pattern, and all of these results are described in statistical parameters. The results of this study, shear strength, failure area, pattern etc, can provide the direct basement on the design, cutoff angle, support pattern, support strength and etc.

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MRNS 네트워크에서 특수한 메트릭스를 응용한 병렬 경로배정 알고리즘 (Application of the Special Matrices to the Parallel Routing Algorithm on MR NS Network)

  • 최완규;정일용
    • 한국정보처리학회논문지
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    • 제3권1호
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    • pp.55-62
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    • 1996
  • MRNS(Mixed Radix Number System) 네트워크는 슈퍼컴퓨터나 MIMD의 모 델로 널리 쓰이고 있으며 많은 연구가 진행되고 있는 하이퍼큐브의 일반적인 대수학적 모델이다. 본 논문에서는 MRNS 네트워크상에서 메세지의 전송 알고리즘을 연구 하였다. 우리가 이 네트워크상에서 임의의 발신 노드부터 수신노드까지 n개의 패킷들을 동시에 보내려고할 때 이들 패킷들의 빠르고, 안전하게 수신 노도까지 도달하기 위해서는 1번 째의 경로가 다른 모든 경로들로부터 node-disjoint 되어야 한다. 이를 위해 우리는 특수한 메트릭스인 HCLS(Hamiltonian Circuit Latin Squre)[1〕를 응용하여 선형 병렬 전송알고리즘을 개발하였다.

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3D-EMCN법을 이용한 광 픽업 액츄에이터의 해석 및 최적설계 (Analysis and Optimal Design of Optical Pickup Actuator by 3D-EMCN Method)

  • 김진아;전태경
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제51권5호
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    • pp.234-241
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    • 2002
  • An optical pickup actuator is an objective-lens-moving mechanism that provides a means to follow the disk displacement accurately(1). In this paper, a slim type optical pickup actuator for Notebook PCs is analyzed and designed to improve the driving sensitivity A three dimensional equivalent magnetic circuit network method (3D-EMCN method) is proposed for an analysis method which provides better characteristics in both precision and computation time of analysis comparing with a commercial three-dimensional finite element (3D-FEM) codes. To verify the validity of proposed method, we made a comparison between the analysis results and the experimental ones. We also compared this analysis results with 3D-FEM results. Among the several optimal algorithm, we adopt a niching genetic algorithm, which renders a set of the multiple optimal solutions. RCS (Restricted Competition Selection) niching genetic algorithm is used for optimal design of the actuator's performance. Recently, the pickup actuator needs additional driving structure for radial and tangential tilting motion to obtain better pick-up performance. So we applied the proposed method to the model containing tilting coils.

OptiNeural System for Optical Pattern Classification

  • Kim, Myung-Soo
    • Journal of Electrical Engineering and information Science
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    • 제3권3호
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    • pp.342-347
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    • 1998
  • An OptiNeural system is developed for optical pattern classification. It is a novel hybrid system which consists of an optical processor and a multilayer neural network. It takes advantages of two dimensional processing capability of an optical processor and nonlinear mapping capability of a neural network. The optical processor with a binary phase only filter is used as a preprocessor for feature extraction and the neural network is used as a decision system through mapping. OptiNeural system is trained for optical pattern classification by use of a simulated annealing algorithm. Its classification performance for grey tone texture patterns is excellent, while a conventional optical system shows poor classification performance.

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텍셀을 이용한 3차원 물체의 형상 인식 (Shape Recognition of 3-D Object Using Texels)

  • 김도년;조동섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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    • pp.460-464
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    • 1990
  • Texture provides an important source of information about the local orientation of visible surfaces. An important task that arises in many computer vision systems is the reconstruction of three-dimensional depth information from two-dimensional images. The surface orientation of texel is classified by the Artificial Neural Network. The classification method to recognize the shape of 3D object with artificial neural network requires less developing time comparing to conventional method. The segmentation problem is assumed to be solved. The surface in view is smooth and is covered with repeated texture elements. In this study, 3D shape reconstruct using interpolation method.

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3차원 합성곱 신경망 기반 향상된 스테레오 매칭 알고리즘 (Enhanced Stereo Matching Algorithm based on 3-Dimensional Convolutional Neural Network)

  • 왕지엔;노재규
    • 대한임베디드공학회논문지
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    • 제16권5호
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    • pp.179-186
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    • 2021
  • For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.

액정을 이용한 3차원 사각채널 내 혼합대류의 정량적 가시화 (Quantitative Visualization of Mixed Convection in 3-D Rectangular Channels Using TLC Tracers)

  • 박일용;김정수;배대석
    • 동력기계공학회지
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    • 제20권6호
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    • pp.51-57
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    • 2016
  • Experiment is carried out to investigate the mixed convective flow in three-dimensional horizontal rectangular channels filled with high viscous fluid. The particle image velocimetry(PIV) with thermo-sensitive liquid crystal tracers is used for visualizing and analysis. Quantitative data of temperature and velocity are obtained by applying the color-image processing to a visualized image, and neural network is applied to the color-to-temperature calibration. In this study, the fluid used is silicon oil(Pr=909), the aspect ratio(channel width to heigh) is 4 and Reynolds number is $2{\times}10^{-2}$. From the present study, we can visualize the quantitative temperature and velocity of mixed convective flow in three-dimensional horizontal rectangular channels simultaneously.

전화선자 인터텟을 이용한 3차원 원격 모니터링 시스템의 설계 (Design of 3-Dimensional Remote Monitoring System Using Telephone Line and Internet)

  • 양필수;김주환;김성호
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.47-47
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    • 2000
  • Most measuring devices are equipped with RS-232 or GPIB interface for communicating data with computers. If the measuring devices can be accessed by a server computer, the valuable information from the devices can be effectively shared with other computers via internet. But, if the measuring devices and the server computer are too far away, it is difficulty to directly connect them by RS232 interface. PSTN(Public Switched Telephone Network) refers to the world's collection of interconnected voice-oriented public telephone networks. Measuring computer system which is equipped with RS232 interface and modem for PSTN can be introduced to overcome the aforementioned distance problem, In this work, an internet based remote monitoring system which utilizes PSTN and VRML for 3-dimensional GUI is proposed.

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힘제어 기반의 틈새 추종 로봇의 제작 및 제어에 관한 연구 : Part Ⅰ. 신경회로망을 이용한 레이저와 카메라에 의한 틈새 검출 및 로봇 제작 (Implementation and Control of Crack Tracking Robot Using Force Control : Crack Detection by Laser and Camera Sensor Using Neural Network)

  • 조현택;정슬
    • 제어로봇시스템학회논문지
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    • 제11권4호
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    • pp.290-296
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    • 2005
  • This paper presents the implementation of a crack tracking mobile robot. The crack tracking robot is built for tracking cracks on the pavement. To track cracks, crack must be detected by laser and camera sensors. Laser sensor projects laser on the pavement to detect the discontinuity on the surface and the camera captures the image to find the crack position. Then the robot is commanded to follow the crack. To detect crack position correctly, neural network is used to minimize the positional errors of the captured crack position obtained by transformation from 2 dimensional images to 3 dimensional images.