• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1996년도 추계학술대회 논문집
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• pp.316-319
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• 1996

In this study, characteristics of ultrasonic transducer fabricated with porous piezoelectric resonator are investigated, 3-D underwater object recognition using the self-made ultrasonic transducer and SOFM(Self-Organizing Feature Map) neural network are presented. The self-made transducer was satisfied the required condition of ultrasonic transducer in water, and the recognition rates for the training data and the testing data were 100 and 95.3% respectively. The experimental results have shown that the ultrasonic transducer fabricated with porous piezoelectric resonator could be applied for sonar system.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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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).

• 한국음향학회지
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• 제18권3호
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• pp.62-67
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• 1999

본 논문은 회귀신경망을 이용한 음성인식에 관한 연구이다. 예측형 신경망으로 음절단위로 모델링한 후 미지의 입력음성에 대하여 예측오차가 최소가 되는 모델을 인식결과로 한다. 이를 위해서 예측형으로 구성된 신경망에 음성의 시변성을 신경망 내부에 흡수시키기 위해서 회귀구조의 동적인 신경망인 회귀예측신경망을 구성하고 Elman과 Jordan이 제안한 회귀구조에 따라 인식성능을 서로 비교하였다. 음성DB는 ETRI의 샘돌이 음성 데이터를 사용하였다. 그리고, 신경망의 최적모델을 구하기 위하여 예측차수와 은닉층 유니트 수의 변화에 따른 인식률의 변화와 문맥층에서 자기회귀계수를 두어 이전의 값들이 문맥층에서 누적되도록 하였을 경우에 대한 인식률의 변화를 비교하였다. 실험결과, 최적의 예측차수, 은닉층 유니트수, 자기회귀계수는 신경망의 구조에 따라 차이가 나타났으며, 전반적으로 Jordan망이 Elman망보다 인식률이 높았으며, 자기회귀계수에 대한 영향은 신경망의 구조와 계수값에 따라 불규칙하게 나타났다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.346-349
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• 2011

In this paper, we design a perceptually invisible dot pattern layout and its recognition scheme, and we apply the recognition scheme into a smart self learning aid for interactive learning aid. To increase maximum information capacity and also increase robustness to the noises, we design a ECC (error correcting code) based dot pattern with directional vector indicator. To make a smart self-learning aid, we embed the micro dot pattern (20 information bit + 15 ECC bits + 9 layout information bit) using K ink (CMYK) and extract the dot pattern using IR (infrared) LED and IR filter based camera, which is embedded in the smart pen. The reason we use K ink is that K ink is a carbon based ink in nature, and carbon is easily recognized with IR even without light. After acquiring IR camera images for the dot patterns, we perform layout adjustment using the 9 layout information bit, and extract 20 information bits from 35 data bits which is composed of 20 information bits and 15 ECC bits. To embed and extract information bits, we use topology based dot pattern recognition scheme which is robust to geometric distortion which is very usual in camera based recognition scheme. Topology based pattern recognition traces next information bit symbols using topological distance measurement from the pivot information bit. We implemented and experimented with sample patterns, and it shows that we can achieve almost 99% recognition for our embedding patterns.

• 가정과삶의질연구
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• 제24권2호
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• pp.61-71
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• 2006

The purpose of this study was to investigate the relationships between parental childrearing attitude and parental childrearing behavior and the effect of parental childrearing attitude and parental childrearing behavior on children's self-efficacy. The subjects included 293 children from the 4th grade to the 6th grade in two elementary schools in Seoul and Incheon. The results were as follows: First, the subjects recognized the difference between parental childrearing attitude and parental childrearing behavior; Second, the children's self-efficacy varied depending upon the style of parental childrearing attitude and the level of recognition of parental childrearing attitude by the children; Third, the children's self-efficacy varied depending upon the style of parental childrearing behavior and the level of recognition of parental childrearing behavior by the children. Several suggestions were made concerning future parental childrearing attitude and parental childrearing behavior.

• 한국음향학회지
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• 제39권5호
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• pp.483-489
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• 2020

본 논문에서는 저자원 환경의 음성인식에서 음향 모델의 성능을 높이기 위한 음향 모델 학습 방법을 제안한다. 저자원 환경이란, 음향 모델에서 100시간 미만의 학습 자료를 사용한 환경을 말한다. 저자원 환경의 음성인식에서는 음향 모델이 유사한 발음들을 잘 구분하지 못하는 문제가 발생한다. 예를 들면, 파열음 /d/와 /t/, 파열음 /g/와 /k/, 파찰음 /z/와 /ch/ 등의 발음은 저자원 환경에서 잘 구분하지 못한다. 자기 주의 메커니즘은 깊은 신경망 모델로부터 출력된 벡터에 대해 가중치를 부여하며, 이를 통해 저자원 환경에서 발생할 수 있는 유사한 발음 오류 문제를 해결한다. 음향 모델에서 좋은 성능을 보이는 Time Delay Neural Network(TDNN)과 Output gate Projected Gated Recurrent Unit(OPGRU)의 혼합 모델에 자기 주의 기반 학습 방법을 적용했을 때, 51.6 h 분량의 학습 자료를 사용한 한국어 음향 모델에 대하여 단어 오류율 기준 5.98 %의 성능을 보여 기존 기술 대비 0.74 %의 절대적 성능 개선을 보였다.

• 한국정보통신학회논문지
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• 제19권9호
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• pp.2129-2137
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• 2015

국내외적으로 무인자동차에 대한 연구와 개발이 활발히 진행되고 있다. 무인자동차를 성공적으로 구현하기 위해서는 매우 많은 요소 기술들을 필요로 한다. 특히 교통신호등의 검출과 인식 시스템은 무인자동차에서 컴퓨터 비전 기술의 핵심적인 요소기술로 주목 받고 있다. 최근까지 제안된 대부분의 교통 신호등 인식 방식들은 잡음과 환경적인 요소에 따라 의존적인 색깔 성분 분석 방법을 사용함으로써 인식률 개선에 있어 제한적인 성능 특성을 갖고 있다. 본 논문에서는 이러한 기존의 방식의 한계를 극복하기 위해 교통신호등이 갖는 형태학적인 특성을 최대한 고려한 방법을 제안한다. 제안한 방식은 색깔 성분과 사각형 특성, 원형 특성과 같은 형태학적 특성을 동시에 고려함으로써 인식 효율을 크게 증대시킨다. 다양한 모의실험을 통하여 제안한 방식은 교통신호등 인식률뿐만 아니라 오인식률 성능을 크게 개선시킬 수 있음을 보인다.

• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.100-105
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• 2021

Contactless service is rapidly emerging as a new growth strategy due to consumers who are reluctant to the face-to-face situation in the global pandemic of coronavirus disease 2019 (COVID-19), and various technologies are being developed to support the fast-growing contactless service market. In particular, the restaurant industry is one of the most desperate industrial fields requiring technologies for contactless service, and the representative technical case should be a kiosk, which has the advantage of reducing labor costs for the restaurant owners and provides psychological relaxation and satisfaction to the customer. In this paper, we propose a solution to the restaurant's store operation through the unmanned kiosk using a state-of-the-art artificial intelligence (AI) technology of image recognition. Especially, for the products that do not have barcodes in bakeries, fresh foods (fruits, vegetables, etc.), and autonomous restaurants on highways, which cause increased labor costs and many hassles, our proposed system should be very useful. The proposed system recognizes products without barcodes on the ground of image-based AI algorithm technology and makes automatic payments. To test the proposed system feasibility, we established an AI vision system using a commercial camera and conducted an image recognition test by training object detection AI models using donut images. The proposed system has a self-learning system with mismatched information in operation. The self-learning AI technology allows us to upgrade the recognition performance continuously. We proposed a fully automated payment system with AI vision technology and showed system feasibility by the performance test. The system realizes contactless service for self-checkout in the restaurant business area and improves the cost-saving in managing human resources.

• 한국컴퓨터정보학회논문지
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• 제22권9호
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• pp.125-132
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• 2017

The purpose of this study was to examine the factors influencing career preparation behavior based on the perception of college students from the perspective of social cognitive career theory and to examine the effect of career barriers and career decision self - efficacy on career preparation behavior And career - decision self - efficacy. The results of the study are as follows. First, career barriers perceived by college students showed a significant positive correlation with career decision self - efficacy and career preparation behavior(-), and career decision efficacy showed a statistically significant correlation with career preparation behavior(+). Second, as a result of linear regression analysis to examine the effect of career barriers on career preparation behavior, lack of self - clarification, lack of job information, and lack of recognition of need were subordinate factors of career barriers. Third, as a result of linear regression analysis to examine the effect of career decision - making self - efficacy on career preparation behavior, goal setting and job information, which are sub - factors of career decision self - efficacy, were analyzed. Fourth, mediating effects of career decision self - efficacy on career barriers and career preparation behavior were analyzed by hierarchical regression analysis. The results of this study confirm that the level of career barrier, which is an important factor in career preparation behavior of college students, should be lowered and career decision self - efficacy should be increased.

• 분석과학
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• 제18권6호
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• pp.460-468
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• 2005

The biotin-avidin complex, as a model recognition system, has been constructed through N-hydroxysuccinimide(NHS) reaction on a variety of substrates such as a smooth Au film, electrochemically roughened Au electrode and chemically modified mica. Stepwise self-assembled monolayers (SAMs) of biotin-avidin system were characterized by surface-enhanced resonance Raman scattering (SERRS) spectroscopy, atomic force microscopy (AFM) and surface plasmon resonance (SPR). A strong SERRS signal of rhodamine tags labeled in avidin from the SAMs on a roughened gold electrode indicated the successful complex formation of stepwise biotin-avidin recognition system. AFM images showed the circular shaped avidin aggregates (hexamer) with ca. $60{\AA}$ thick on the substrate, corresponding to one layer of avidin. The surface coverage and concentration of avidin molecules were estimated to be 90% and $7.5{\times}10^{-12}mol/cm^2$, respectively. SPR technique allowed one to monitor the surface reaction of the specific recognition with high sensitivity and precision.