• International Journal of Precision Engineering and Manufacturing
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• 제4권1호
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• pp.43-48
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• 2003

A linear laser-vision sensor called ‘Perception TriCam Contour' is mounted on an industrial robot and often used for various application of the robot such as the position correction and the inspection of a part. In this paper, a sensor center position calibration is presented for the most accurate use of the robot-Perceptron system. The obtained algorithm is suitable for on-site calibration in an industrial application environment. The calibration algorithm requires the joint sensor readings, and the Perceptron sensor measurements on a specially devised jig which is essential for this calibration process. The algorithm is implemented on the Hyundai 7602 AP robot, and Perceptron's measurement accuracy is increased up to less than 1.4mm.

• 한국정밀공학회지
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• 제16권2호통권95호
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• pp.176-182
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• 1999

This paper presents a new autonomous kinematic calibration technique by using a laser-vision sensor called "Perceptron TriCam Contour". Because the sensor measures by capturing the image of a projected laser line on the surface of the object, we set up a long, straight line of a very fine string inside the robot workspace, and then allow the sensor mounted on a robot to measure the point intersection of the line of string and the projected laser line. The point data collected by changing robot configuration and sensor measuring are constrained to on a single straght line such that the closed-loop calibration method can be applied. The obtained calibration method is simple and accurate and also suitable for on-site calibration in an industrial environment. The method is implemented using Hyundai VORG-35 for its effectiveness.

• Journal of Biosystems Engineering
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• 제43권4호
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• pp.352-361
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• 2018

Purpose: The objective of this study was to develop a multilayer perceptron (MLP) model to estimate solar radiation using a solar module. Methods: Data for the short-circuit current of a solar module and other environmental parameters were collected for a year. For MLP learning, 14,400 combinations of input variables, learning rates, activation functions, numbers of layers, and numbers of neurons were trained. The best MLP model employed the batch backpropagation algorithm with all input variables and two hidden layers. Results: The root-mean-squared error (RMSE) of each learning cycle and its average over three repetitions were calculated. The average RMSE of the best artificial neural network model was $48.13W{\cdot}m^{-2}$. This result was better than that obtained for the regression model, for which the RMSE was $66.67W{\cdot}m^{-2}$. Conclusions: It is possible to utilize a solar module as a power source and a sensor to measure solar radiation for an agricultural sensor node.

• 대한토목학회논문집
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• 제26권4A호
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• pp.639-645
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• 2006

FRP(Fiber Reinforced Polymer)는 부식의 저항성, 고강도, 피로저항 능력 및 성형성 등에서 우수한 건설 신소재이다. 광섬유 브래그 격자(Fiber Bragg Grating; FBG) 센서는 전자기 저항, 작은 소재의 크기, 그리고 높은 내구성 등의 이점으로 smart sensor로서 현재 많이 사용되고 있다. 하지만 FBG 센서의 변위 측정 기술 능력의 부족으로 현재까지는 변형률, 온도 등의 물리량 측정센서로서 활용되고 있는 실정이다. 본 연구에서는 FRP와 FBG센서의 기능 복합화(Hybrid)를 통하여 smart FRP Rod를 개발 한 후 인장시험을 실시하였다. 또한, FBG센서에 의해 측정된 변형률 데이터를 신경망(Neural Network) 기법을 이용하여 변위 추정 모형을 개발함으로서 FBG 센서 단점인 변형률 계측만을 위한 센싱 역할을 극복하고자 한다. 인공신경망 모형은 MLP(Multi-layer Perceptron)로, 오차범위 0.001에 수렴 될 수 있도록 학습(training)을 실시하였다. 학습에는 비선형 목적함수와 역전파 학습(Back-propagation) 알고리즘을 적용하였으며 모형의 검증은 UTM에서 측정된 변위 값과 수치해석에 의한 결과 값을 비교함으로서 실시하였다.

• 전자공학회논문지B
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• 제30B권2호
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• pp.69-77
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• 1993

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

• 센서학회지
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• 제11권4호
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• pp.239-246
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• 2002

In this paper a new design of multi-layer perceptron(MLP) for camera calibration is proposed. Most existing techniques determine a transformation from 3D spatial points to their image points and camera parameters are tried to be estimated from the transformation. The technique proposed here, on the other hand, determines rays of sight uniquely from image points and parameters are estimated from the relationship using an MLP. By this approach projection and back-projection can be done more straightforwardly. Being based on a geometric model, a network design process becomes less ambiguous, which is a clear merit compared to other neural net based techniques. An MLP designed according to the technique proposed showed fast and stable learning in tests under various conditions.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.920-922
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• 2018

This paper describes a method to classify simple circular artificial markers on surfaces of a box on the back of hand to detect the pose of user's hand for VR/AR applications by using a Leap Motion camera and two IMU sensors. One IMU sensor is located in the box and the other IMU sensor is fixed with the camera. Multi-layer Perceptron (MLP) algorithm is adopted to classify artificial markers on each surface tracked by the camera using IMU sensor data. It is experimented successfully in real-time, 70Hz, under PC environments.

• 한국인터넷방송통신학회논문지
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• 제12권4호
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• pp.23-29
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• 2012

사람들이 신체를 다친 경우 의료기관에서 치료를 것이 보통이다. 하지만 몇몇 환부에 따라서 추가적인 재활이 필요한 경우도 존재한다. 이러한 의료기관은 규모에 따른 재활프로그램에 큰 차이가 있으며, 규모가 작은 대개의 의료기관의 재활프로그램은 의사와 환자의 구두로 진행이 되는 것이 문제점이다. 따라서 본 논문에서는 이러한 소규모 의료기관에서의 재활치료에 정확도와 신뢰성을 보조하기 위해서 신체의 접촉과 힘을 계측할 수 있는 센서들을 대체 및 조합하여 촉각 센서와 유사한 기능을 가지는 대체 촉각 센서를 제안한다. 본 논문에서는 퍼셉트론 신경망을 적용시켜 접촉 평가를 패턴에 따라 확인하는 알고리즘을 적용하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.360-364
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• 2009

현대사회는 인구의 고령화에 따른 노인인구의 증가 및 만성질환자의 증가에 따른 의료수요 급증이 예상되고 있다. 하지만 현재의 의료서비스 인프라는 증가하는 의료수요를 충족하기에는 역부족이 따르며, 이러한 문제점을 해결하기위해 정보통신기술과 헬스케어기술이 결합된 유비쿼터스 헬스케어기술이 부각되고 있다. 본 연구에서는 일상생활 중 움직임에 따른 활동 상태를 판별하여 운동량의 모니터링을 통한 건강관리뿐만 아니라 낙상 등과 같은 응급상황의 모니터링이 가능한 시스템을 구현하고자 하였다. 이를 위하여 3축 가속도센서를 이용하여 인체의 움직임에 따른 활동 가속도 신호를 계측할 수 있는 센서 및 시스템을 구현하였다. 또한 계측된 센서신호를 PC또는 휴대용 단말기로 무선전송하기위하여 무선센서네트워크 기술을 적용한 데이터 전송시스템을 구현하였다. 계측된 가속도 신호로부터 활동 상태를 판별하기위해 다층 퍼셉트론 알고리즘을 적용한 분류알고리즘을 제안하였으며, 분류알고리즘의 성능평가를 통해 실제 활동상태 모니터링에 적용 가능함을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.210-210
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• 2000

In this paper, we have investigated the properties of multi-layer perceptron (MLP) for odour patterns classification and concentration estimation simultaneously. When the MLP may be has a fast convergence speed with small error and excellent mapping ability for classification, it can be possible to use for classification and concentration prediction of volatile chemicals simultaneously. However, the conventional MLP, which is back-Propagation of error based on the steepest descent method, was difficult to use for odour classification and concentration estimation simultaneously, because it is slow to converge and may fall into the local minimum. We adapted the Levenberg-Marquardt(LM) algorithm [4,5] having advantages both the steepest descent method and Gauss-Newton method instead of the conventional steepest descent method for the simultaneous classification and concentration estimation of odours. And, We designed the artificial odour sensing system(Electronic Nose) and applied LM-BP algorithm for classification and concentration prediction of VOC gases.