• 제목/요약/키워드: Multi-Modal

검색결과 630건 처리시간 0.024초

대중교통순석을 위한 교통망작성기법 (On the Large Area Multi Modal Network Formulation Techniques)

  • 강위훈
    • 대한교통학회지
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    • 제1권1호
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    • pp.48-55
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    • 1983
  • One of the major objectives of a transportation study is to provide the transportation networks for future years in order to accommodate the projected transport demand for the movement of passengers and goods utilizing the optimum "mix" of modes. To achieve this goal, the planning process starts with collection and analysis of data to determine the existing traffic demand and travel pattern, and to assign the future trip interchanges on th existing and planned networks to determine areas of improvements so that it can cope with increasing future traval demand. The purpose of this paper attempts to explain the public transport network formulation techniques which can be easily applied to the large urban area multi modal public transport system.

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IoT를 위한 음성신호 기반의 톤, 템포 특징벡터를 이용한 감정인식 (Emotion Recognition Using Tone and Tempo Based on Voice for IoT)

  • 변성우;이석필
    • 전기학회논문지
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    • 제65권1호
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    • pp.116-121
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    • 2016
  • In Internet of things (IoT) area, researches on recognizing human emotion are increasing recently. Generally, multi-modal features like facial images, bio-signals and voice signals are used for the emotion recognition. Among the multi-modal features, voice signals are the most convenient for acquisition. This paper proposes an emotion recognition method using tone and tempo based on voice. For this, we make voice databases from broadcasting media contents. Emotion recognition tests are carried out by extracted tone and tempo features from the voice databases. The result shows noticeable improvement of accuracy in comparison to conventional methods using only pitch.

홍채인식과 얼굴인식을 이용한 다중생체인식 (Multi-Modal Biometrics Recognition Using the Iris Recognition and Face Recognition)

  • 유병진;고현주;권만준;전명근
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2005년도 추계학술발표대회 및 정기총회
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    • pp.427-430
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    • 2005
  • 본 연구는 기존 단일 생체인식의 단점을 보완하기 위해 다중생체인식(Multi-Modal Biometrics Recognition)기법을 연구한 것으로, 홍채영상을 이용한 홍채인식과 얼굴영상을 이용한 얼굴인식을 융합하기 위해 다양한 방법을 시도해 보았다. 이에, CBNU 홍채 영상데이터를 사용한 홍채인식은 Gabor Wavelet과 FLDA(Fuzzy Linear Discriminant Analysis)를 이용하였으며, FERET 얼굴영상데이터를 사용한 얼굴인식도 FLDA를 이용하여 패턴의 특징을 추출하고 matching에 따른 score를 각각 획득한다. 얻어진 두 score 값에 대하여 다양한 균등화과정을 사용해 보았으며, 다중생체인식 융합방법중 하나인 Weight sum rule을 적용하여 인식률을 얻었다. 또한, 단일 생체인식의 경우보다 좋은 성능을 나타냄을 확인하기 위해 FRR과 FAR등의 인식률 평가방법을 사용하였으며, 기존 단일생체인식 방법보다 좋은 성능을 보이고 있음을 확인할 수 있었다.

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Improved MCMC Simulation for Low-Dimensional Multi-Modal Distributions

  • Ji, Hyunwoong;Lee, Jaewook;Kim, Namhyoung
    • Management Science and Financial Engineering
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    • 제19권2호
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    • pp.49-53
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    • 2013
  • A Markov-chain Monte Carlo sampling algorithm samples a new point around the latest sample due to the Markov property, which prevents it from sampling from multi-modal distributions since the corresponding chain often fails to search entire support of the target distribution. In this paper, to overcome this problem, mode switching scheme is applied to the conventional MCMC algorithms. The algorithm separates the reducible Markov chain into several mutually exclusive classes and use mode switching scheme to increase mixing rate. Simulation results are given to illustrate the algorithm with promising results.

얼굴과 지문을 결합한 다중 생체인식 시스템의 실험적 연구 (An Empirical Study of Multi-Modal Biometrics using Face and Fingerprint)

  • 강효섭;한영찬;김학일
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (2)
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    • pp.622-624
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    • 2002
  • 생체인식 기술은 급속도로 발전하고 있지만 개개의 생체 정보를 이용한 단일 생체인식 기술은 생체 방식에 따라 각각의 문제점이 노출되고 있는 상황이다. 이에 두 가지 이상의 생체 정보를 결합하여 단일 생체인식 기술의 문제점을 극복하고 보다 좋은 인식률을 확보하기 위해 다중 생체인식 시스템(Multi-Modal Bio-metries System)이라는 복합 시스템이 제안 되었다. 이 논문에서는 생체인식 산업의 특성 및 개인 인증 방법으로 사용중인 단일 생체인식 시스템의 문제점을 알아보고 그 해결방안으로 다중 생체인식 시스템의 확률단계(Probability Level)에서 더 좋은 성능을 보여주기 위해 각각의 시스템에 가중치(Weight)를 부여 할 경우, EER(Equal Error Rate)이 단일 생체인식 시스템에 보다 가중치를 부여 했을 때 낮아짐과 동시에 ROC 커브도 (Receiver Operating Characteristic Curve) 좋아짐을 보였다.

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Multiple Emission States in Active Galactic Nuclei

  • 박종호
    • 천문학회보
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    • 제38권1호
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    • pp.45-45
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    • 2013
  • We present a test of the emission statistics of active galactic nuclei (AGN), probing the connection between the red-noise temporal power spectra and multi-modal flux distributions known from observations. We simulate AGN lightcurves under the assumption of uniform stochastic emission processes for different power-law indices of their respective power spectra. For sufficiently shallow slopes (power-law indices beta ${\leq}$ 1.0), the flux distributions (histograms) of the resulting lightcurves are approximately Gaussian. For indices corresponding to steeper slopes (beta ${\geq}$ 1.0), the flux distributions become multi-modal. This finding disagrees systematically with result of recent mm/radio observations. Accordingly, we conclude that the emission from AGN does not necessarily originate from uniform stochastic processes even if their power spectra suggest otherwise. Possible mechanisms include transitions between different activity states and/or the presence of multiple, spatially disconnected, emission regions.

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Object Tracking for a Video Sequence from a Moving Vehicle: A Multi-modal Approach

  • Hwang, Tae-Hyun;Cho, Seong-Ick;Park, Jong-Hyun;Choi, Kyoung-Ho
    • ETRI Journal
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    • 제28권3호
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    • pp.367-370
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    • 2006
  • This letter presents a multi-modal approach to tracking geographic objects such as buildings and road signs in a video sequence recorded from a moving vehicle. In the proposed approach, photogrammetric techniques are successfully combined with conventional tracking methods. More specifically, photogrammetry combined with positioning technologies is used to obtain 3-D coordinates of chosen geographic objects, providing a search area for conventional feature trackers. In addition, we present an adaptive window decision scheme based on the distance between chosen objects and a moving vehicle. Experimental results are provided to show the robustness of the proposed approach.

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A PROPOSAL OF ENHANSED NEURAL NETWORK CONTROLLERS FOR MULTIPLE CONTROL SYSTEMS

  • Nakagawa, Tomoyuki;Inaba, Masaaki;Sugawara, Ken;Yoshihara, Ikuo;Abe, Kenichi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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    • pp.201-204
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    • 1998
  • This paper presents a new construction method of candidate controllers using Multi-modal Neural Network(MNN). To improve a control performance of multiple controller, we construct, candidate controllers which consist of MNN. MNN can learn more complicated function than multilayer neural network. MNN consists of preprocessing module and neural network module. The preprocessing module transforms input signals into spectra which are used as input of the following neural network module. We apply the proposed method to multiple control system which controls the cart-pole balancing system and show the effectiveness of the proposed method.

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MULTIPLE EMISSION STATES IN ACTIVE GALACTIC NUCLEI

  • Park, Jong-Ho;Trippe, Sascha
    • 천문학회지
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    • 제45권6호
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    • pp.147-156
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    • 2012
  • We present a test of the emission statistics of active galactic nuclei (AGN), probing the connection between the red-noise temporal power spectra and multi-modal flux distributions known from observations. We simulate AGN lightcurves under the assumption of uniform stochastic emission processes for different power-law indices of their respective power spectra. For sufficiently shallow slopes (power-law indices (${\beta}{\leq}1$), the flux distributions (histograms) of the resulting lightcurves are approximately Gaussian. For indices corresponding to steeper slopes (${\beta}{\geq}1$), the flux distributions become multi-modal. This finding disagrees systematically with results of recent mm/radio observations. Accordingly, we conclude that the emission from AGN does not necessarily originate from uniform stochastic processes even if their power spectra suggest otherwise. Possible mechanisms include transitions between different activity states and/or the presence of multiple, spatially disconnected, emission regions.

실외에서 로봇의 인간 탐지 및 행위 학습을 위한 멀티모달센서 시스템 및 데이터베이스 구축 (Multi-modal Sensor System and Database for Human Detection and Activity Learning of Robot in Outdoor)

  • 엄태영;박정우;이종득;배기덕;최영호
    • 한국멀티미디어학회논문지
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    • 제21권12호
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    • pp.1459-1466
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    • 2018
  • Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.