• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.671-674
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• 1999

We report the new method for speaker recognition. Until now, many researchers have used HMM (Hidden Markov Model) with cepstral coefficient or neural network for speaker recognition. Here, we introduce the method of speaker recognition using eigenspace. This method can reduce the training and recognition time of speaker recognition system. In proposed method, we use the low rank model of the speech eigenspace. In experiment, we obtain good recognition result.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.55.3-55
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• 2001

The implementation of human-like robot has been advanced in various parts such as mechanic arms, legs, and applications of five senses. The vision applications have been developed in several decades and especially the face recognition have become a prominent issue. In addition, the development of computer systems makes it possible to process complex algorithms in realtime. The most of human recognition systems adopt the discerning method using fingerprint, iris, and etc. These methods restrict the motion of the person to be discriminated. Recently, the researchers of human recognition systems are interested in facial recognition by using machine vision. Thus, the object of this paper is the implementation of the realtime ...

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.2
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• pp.65-70
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• 2003

In this study, researchers developed the estimative algorithm for artificial defect in semiconductor packages and performed it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Backpropagation Neural Network. Self-organizing Map and Backpropagation Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages : Crack, Delamination and Normal. According to the results, we were confirmed that estimative algerian was provided the recognition rates of 75.7% (for Crack) and 83.4% (for Delamination) and 87.2 % (for Normal).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.91-96
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• 2005

In this study, researchers developed the estimative algorithm for artificial defects in semiconductor packages and performed it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Backpropagation Neural Network. Self-Organizing Map and Backpropagation Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages: Crack, Delamination and Normal. According to the results, we were confirmed that estimative algorithm was provided the recognition rates of $75.7\%$ (for Crack) and $83_4\%$ (for Delamination) and $87.2\%$ (for Normal).

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.25-28
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• 2002

This paper introduce a personalized facial expression recognition system. Many previous works on facial expression recognition system focus on the formal six universal facial expressions. However, it is very difficult to make such expressions for normal person without much effort and training. And in these days, the personalized service is also mainly focused by many researchers in various fields. Thus, we Propose a novel facial expression recognition system with fuzzy neural networks and robust image processing.

• MALSORI
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• no.51
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• pp.151-165
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• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.

• Journal of Sasang Constitutional Medicine
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• v.23 no.4
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• pp.514-525
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• 2011

1. Objectives This study aims to find out identify the recognition and attitude about the research ethic among Constitutional medicine researchers. 2. Methods This survey was conducted to the 37 researchers who were currently participating in Korea Constitution Multicenter Study guided by Korea institute of Oriental medicine(KIOM). The survey consist of 4 parts that level of acknowledgment about the systems and laws on clinical research ethic, clinical research experiences and education, the level of acknowledgment about Institutional Review Board(IRB) and the recognition about overall research ethic. 3. Results Thirty one questionnaires were collected. Most researchers had low level of acknowledgment about the guidelines of basic research ethic. It was proved that more than 65% of the respondents have never received education for clinical research ethic. Moreover, 70% of them felt the need for education of clinical research ethic. In addition, most of the respondents recognized the fact that IRB is responsible for ethically implementing clinical research. 39% of the researchers thought that they themselves have a firm ethical viewpoint, while the rest of the group showed somewhat difficulty on their own ethical implementation of clinical research. 4. Conclusions Most of researcher had partial awareness of regulations and laws on clinical research ethic. And Educational needs of research ethic was high. Therefore education and Public Relations need to be done to extend research ethic. Moreover, standardized course of education on research ethic should be developed and activated.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.322-327
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• 2007

Researchers in the field of psychology used Electroencephalographic (EEG) to record activities of human brain lot many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study emotion recognition method which uses one of physiological signals and gestures in the existing research. In this paper, we use together physiological signals and gestures for emotion recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both physiological signals and gestures gets high recognition rates better than using physiological signals or gestures. Both physiological signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.927-939
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• 2020

Gait recognition can identify people's identity from a long distance, which is very important for improving the intelligence of the monitoring system. Among many human features, gait features have the advantages of being remotely available, robust, and secure. Traditional gait feature extraction, affected by the development of behavior recognition, can only rely on manual feature extraction, which cannot meet the needs of fine gait recognition. The emergence of deep convolutional neural networks has made researchers get rid of complex feature design engineering, and can automatically learn available features through data, which has been widely used. In this paper,conduct feature metric learning in the three-dimensional space by combining the three-dimensional convolution features of the gait sequence and the Siamese structure. This method can capture the information of spatial dimension and time dimension from the continuous periodic gait sequence, and further improve the accuracy and practicability of gait recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.772-776
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• 2006

A research about facial image recognition is studied in the most of images in a full race. A representative part, effecting a facial image recognition, is eyes and a mouth. So, facial image recognition researchers have studied under the central eyes, eyebrows, and mouths on the facial images. But most people in front of a camera in everyday life are difficult to recognize a fast change of pupils. And people wear glasses. So, in this paper, we try using Principal Component Analysis(PCA) for facial image recognition in blindfold case.