• Title/Summary/Keyword: recognition-rate

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IT Export-Import Fuction Estimation and MRA Effect (정보통신기기 산업의 대미 수출입 함수 추정을 통한 MRA효과)

  • Lim, Kwang-Sun;Park, Yong-Jadse
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.131-134
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    • 2007
  • From January 2000 to September 2006, we use the 81 months of the data to estimate the exportation and importation function of the Korea information communications main device industry towards to U.S., and through this process we extract the cost elasticity. And from cost elsticity, we estimate the exportation and importation enlarging effect between Korea and U.S assumption of the exportation and importation reduction rate was givien to MRA contract between Korea and U.S.

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Real-Time Recognition of the Korean Spingle Vowels Using the Speech Spectrum Anaysis (음성 스펙트럼 분석에 의한 한국어 단모음 실시간 인식)

  • 김엄준;성미영
    • Proceedings of the Korea Multimedia Society Conference
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    • 1998.10a
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    • pp.226-231
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    • 1998
  • 본 연구에서는 짧은 시간에 계산이 가능하며, 음성을 특징 지울 수 있는 파라미터로서 영 교차율(zero crossing rate), 단 구간 에너지(short-term, energy) 그리고 포만트(formant)를 사용하였다. 특정 화자의 음성을 입력 받아서 단모음인 'ㅏ, ㅐ, ㅓ, ㅔ, ㅗ, ㅜ, ㅡ. ㅣ'에 대한 인식을 위해 위의 세가지 파라미터를 측정하였다. 영 교차율과 단 구간 에너지 파라미터는 유성음과 무성음의 구별과 음성인지 아닌지를 판별하는데 사용하였다. 포만트 파라미터는 10차 켑스트럼(cepstrum)을 이용하여 구하였으며, 각 단모음을 판별하기 위해서 사용하였다. 하나의 단모음을 입력받아 처리하여 텍스트로 출력하는데 평균 0.065sec에 처리하며, 각각의 단모음에 대해 93%, 10개의 테스트 문장에 대해 72%의 인식률을 보이고 있다.

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Vehicle Manufacturer Recognition using Deep Learning and Perspective Transformation

  • Ansari, Israfil;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.6 no.4
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    • pp.235-238
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    • 2019
  • In real world object detection is an active research topic for understanding different objects from images. There are different models presented in past and had significant results. In this paper we are presenting vehicle logo detection using previous object detection models such as You only look once (YOLO) and Faster Region-based CNN (F-RCNN). Both the front and rear view of the vehicles were used for training and testing the proposed method. Along with deep learning an image pre-processing algorithm called perspective transformation is proposed for all the test images. Using perspective transformation, the top view images were transformed into front view images. This algorithm has higher detection rate as compared to raw images. Furthermore, YOLO model has better result as compare to F-RCNN model.

A Power Quality Monitoring system using wavelet based RBF network (웨이블릿 기반의 RBF 신경망을 이용한 전력품질 진단시스템)

  • Kim Hong kyun;Lee Jinmok;Choi Jeaho;Lee Sanghoon;Kim Jaesig
    • Proceedings of the KIPE Conference
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    • 2004.07b
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    • pp.858-861
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    • 2004
  • This paper presents a wavelet-based neural network technology for the detection and classification of the various types of power quality disturbances. Power quality phenomena are short-time problems and of many varieties. Particularly, the transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting and classifying transient signals at the same time and in an automatic combines the properties of the wavelet transform and the advantages of neural networks. Especially, the additional feature extraction to improve the recognition rate is considered. The configuration of the hardware of WN (PQ-DAS) and some case studies are described.

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Implementation of an Adaptive Genetic Algorithm Processor for Evolvable Hardware (진화 시스템을 위한 유전자 알고리즘 프로세서의 구현)

  • 정석우;김현식;김동순;정덕진
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.4
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    • pp.265-276
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    • 2004
  • Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.

Gaze Direction Estimation Method Using Support Vector Machines (SVMs) (Support Vector Machines을 이용한 시선 방향 추정방법)

  • Liu, Jing;Woo, Kyung-Haeng;Choi, Won-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.4
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    • pp.379-384
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    • 2009
  • A human gaze detection and tracing method is importantly required for HMI(Human-Machine-Interface) like a Human-Serving robot. This paper proposed a novel three-dimension (3D) human gaze estimation method by using a face recognition, an orientation estimation and SVMs (Support Vector Machines). 2,400 images with the pan orientation range of $-90^{\circ}{\sim}90^{\circ}$ and tilt range of $-40^{\circ}{\sim}70^{\circ}$ with intervals unit of $10^{\circ}$ were used. A stereo camera was used to obtain the global coordinate of the center point between eyes and Gabor filter banks of horizontal and vertical orientation with 4 scales were used to extract the facial features. The experiment result shows that the error rate of proposed method is much improved than Liddell's.

An Improved Cancelable Fingerprint Template Encryption System Research

  • Wang, Feng;Han, Bo;Niu, Lei;Wang, Ya
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.2237-2253
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    • 2017
  • For the existing security problem based on Fuzzy Vault algorithm, we propose a cancelable fingerprint template encryption scheme in this paper. The main idea is to firstly construct an irreversible transformation function, and then apply the function to transform the original template and template information is stored after conversion. Experimental results show it effectively prevents the attack from fingerprint template data and improves security of the system by using minutiae descriptor to encrypt abscissa of the vault. The experiment uses public FVC2004 fingerprint database to test, result shows that although the recognition rate of the proposed algorithm is slightly lower than the original program, but the improved algorithm security and complexity are better, and therefore the proposed algorithm is feasible in general.

A Study on the Contents of Low Birthrate Measures by the Government and Their Effectiveness (저출산 문제에 대한 대책 연구)

  • Choi, Nam-Sook
    • Journal of Family Resource Management and Policy Review
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    • v.11 no.1
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    • pp.53-63
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    • 2007
  • This study analyzes the contents of low birthrate measures by the government and their effectiveness. The discussion on the measures being promoted by the government is conducted by considering the analysis on the cause of low birthrates, introduction of overseas policies and government policy propositions, etc. The evaluation on effectiveness is conducted by considering the recognition of the policies by women who are the subject of childbirth and preceding studies. Low birth rates are not the problem of an individual anymore, but a task that the whole of society has to resolve. The comprehensive measures should be made including the elements that influence birth rate such as reducing the cost of raising a child, creating a favorable environment in society and worksite, and improving the nurturing environment, etc.

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PD Classification by Neural Networks in Specimen of XLPE Power Cable (XLPE 전력용 케이블 시편의 부분방전원 분류)

  • 박성희;이강원;강성화;임기조
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.17 no.8
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    • pp.898-903
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    • 2004
  • In this paper, neural networks is studied to apply as a PD source classification in XLPE power cable specimen. For treeing discharge sources in the specimen, three defected models are made. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

Pedestrian Detection using RGB-D Information and Distance Transform (RGB-D 정보 및 거리변환을 이용한 보행자 검출)

  • Lee, Ho-Hun;Lee, Dae-Jong;Chun, Myung-Geun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.65 no.1
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    • pp.66-71
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    • 2016
  • According to the development of depth sensing devices and depth estimation technology, depth information becomes more important for object detection in computer vision. In terms of recognition rate, pedestrian detection methods have been improved more accurately. However, the methods makes slower detection time. So, many researches have overcome this problem by using GPU. Here, we propose a real-time pedestrian detection algorithm that does not rely on GPU. First, the depth-weighted distance map is used for detecting expected human regions. Next, human detection is performed on the regions. The performance for the proposed approach is evaluated and compared with the previous methods. We show that proposed method can detect human about 7 times faster than conventional ones.