• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 한국방송공학회 2011년도 추계학술대회
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• pp.19-22
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• 2011

본 논문에서는 대표적인 특징점 추출 알고리즘인 SURF (Speeded Up Robust Features)와 얼굴인식에서 널리 쓰이는 Gabor 기술어를 이용한 얼굴 인식 방법을 소개한다. SURF 기반 영상인식 방법은 특징점을 찾고 해당 특징점에서 기술어를 추출한 후, 정합을 수행한다. 본 논문에서는 SURF 를 통해 추출한 특징점에서 Gabor 웨이블릿 변환을 사용해 기술어를 추출하는 얼굴인식 방법을 제안한다. 잘 알려진 ORL 데이터베이스에서의 실험에서 제안한 방법이 기존 SURF 기반의 얼굴 인식 방법에 비해 더 높은 얼굴 인식 성능을 보여줄 뿐 아니라 정합시간을 포함한 처리 속도면에서도 더 우수한 성능을 보였다. 이러한 실험 결과를 통하여 제안하는 방법이 SURF 보다 얼굴 인식에 적합함을 확인할 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• 제18권3호
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• pp.373-380
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• 2008

So far there have been many researches on machine-based recognition of handwritten digit. But we have not yet attained the level of performance that can be satisfactory to men. The dissatisfaction with the performance of machine comes from not only the low accuracy of recognition but also the dissimilarity of the recognition results between man and machine. To reduce the difference of machine from man we first made an experiment with the human recognition of handwritten digits and then inquiry into the way of the human recognition that makes the results of men different from that of machine. We found out the attributes that play an important role in the human recognition process through the analysis of the experimental results like uni- and bi-directional confused pairs of digits, several ones unmixed up with another and the redundancy of mis-recognition, and proposed the approach direction to be able to improve the accuracy of the machine-based recognition, and furthermore the similarity in the recognition results of men and machine on the basis of the found facts above.

• Journal of The Korean Association For Science Education
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• 제23권3호
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• pp.254-264
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• 2003

Researches on laboratory work show that students often achieve little meaningful learning through laboratory work. One reason for this failure is that students often do not know the different types of laboratory work and the 'purposes' of them. Therefore, this study investigated middle school student' ideas about the purposes of laboratory work. To seventh grade students(n=147) of middle school in Seoul, Korea, we asked (Question 1) "Why do scientists do laboratory work?" and (Question 2) "Why do you do laboratory work in science classes?" It was required a short essay including the reasons and examples of them. From the results, it was found that 56.8% of the students had ideas that scientists do laboratory work for discovering new facts or inventing something, and 82.9% of the students responded that they do laboratory work for understanding and memorizing the contents of science textbook. In addition, the differences according to gender and to school achievement level, and the relationship between the ideas about scientists' laboratory work and about school science laboratory work were examined. The results showed that boys responded 'social usefulness' more frequently than girl, while girls mentioned 'personal pleasure' more frequently than boys in relation to the purposes of scientists' laboratory work(p<.05). According to the achievement level, it was founded that 'middle' level students replied 'to remember' more frequently than high and low levels in relation to school science laboratory work. Finally, students who had ideas that scientists do laboratory work for verifying a theory had the similar ideas about school science laboratory work. In conclusion, students are lack of diverse and proper views about laboratory work. It is recommended that teacher need to make clear the purpose of laboratory work and help students to understand of it.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제41권3호
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• pp.201-207
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• 2004

This paper is a study on the recognition of continuous speech and uses a method of speech recognition using syntactic analysis and one-stage DMS/DP. In order to perform the speech recognition, first of all, we make DMS model by section division algorithm and let continuous speech data be recognized through One-stage DMS/DP method using syntactic analysis. Besides the speech recognition experiments of proposed method, we experiment the conventional one-stage DP method under the equivalent environment of data and conditions. From the recognition experiments, it is shown that Ole-stage DMS/DP using syntactic analysis is superior to conventional method.

• The Journal of the Acoustical Society of Korea
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• 제10권2호
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• pp.23-28
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• 1991

This paper is a study on isolated word recognition by independent speaker, we propose DTW speech recognition system by modified dynamic averaging method as reference pattern. 57 city names are selected as recognition vocabulary and 2th LPC cepstrum coefficients are used as the feature parameter. In this paper, besides recognition experiment using modified dynamic averaging method as reference pattern, we perform recognition experiments using causal method, dynamic averaging method, linear averaging method and clustering method with the same data in the same conditions for comparison with it. Through the experiment result, it is proved that recogntion rate by DTW using modified dynamic averaging method is the best as 97.6 percent.

• The Journal of the Acoustical Society of Korea
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• 제18권3호
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• pp.35-42
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• 1999

In this paper, a modified clustering algorithm is proposed to improve the discrimination of discrete HMM(Hidden Markov Model), so that it has increased recognition rate of 2.16% in comparison with the original HMM using the K-means or LBG algorithm. And, for preventing the decrease of recognition rate because of insufficient training data at the training scheme of HMM, a modified probabilistic smoothing method is proposed, which has increased recognition rate of 3.07% for the speaker-independent case. In the experiment applied the two proposed algorithms, the average rate of recognition has increased 4.66% for the speaker-independent case in comparison with that of original VQ/HMM.

• The Journal of the Acoustical Society of Korea
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• 제18권1호
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• pp.86-91
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• 1999

This paper presents the text-prompt method to overcome the weakness of text-dependent and text-independent speaker recognition. Enhanced dynamic time warping for speaker recognition algorithm is applied. For the real-time processing, we use a simple algorithm for end-point detection without increasing computational complexity. The test shows that the weighted-cepstrum is most proper for speaker recognition among various speech parameters. As the experimental results of the proposed algorithm for three prompt words, the speaker identification error rate is 0.02%, and when the threshold is set properly, false rejection rate is 1.89%, false acceptance rate is 0.77% and verification total error rate is 0.97% for speaker verification.

• The Transactions of the Korea Information Processing Society
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• 제4권12호
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• pp.3063-3068
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• 1997

In this paper, we have extended the generalization back-propagation algorithm to multi-layer polynomial higher order neural networks. The purpose of this paper is to describe various pattern recognition using polynomial higher-order neural network. And we have applied shift position T-C test pattern for invariant pattern recognition and measured generalization by mirror symmetry problem. simulation result shows that the ability for invariant pattern recognition increase with the proposed technique. Recognition rate of invariant T-C pattern is 90% effective and of mirror symmetry problem is 70% effective when the proposed technique is utilized. These results are much better than those by the conventional methods.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (B)
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• pp.515-520
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• 2006

계량기 숫자 인식은 일반적으로 사용되고 있는 아날로그 계량기에 카메라를 부착하여, 검침 시 숫자 계기판 영상을 전송받고, 그 영상으로부터 숫자를 추출 및 인식하는 기술이다. 계량기 숫자 인식에서는 카메라의 설치 상태 및 기타 환경적인 요인들로 인해 숫자 계기판 영상의 일관성 있는 취득이 어렵게 된다. 본 논문에서는 숫자 인식에 악영향을 미치는, 취득 영상의 상태 변화를 보정해주기 위해 잡영 제거 및 윤곽보존 숫자강화를 제안하였다. 잡영 제거를 위해 잡영을 분포 위치에 따라서 세 가지 타입으로 나누었으며, 각 타입별로 잡영 제거를 하였다. 윤곽보존 숫자강화 과정에서는 일반적인 이진화 기법이 가지는 테두리 정보손실을 최소화할 수 있도록, 숫자 테두리의 명도를 보존하면서 숫자 중심부분의 밝기를 강화시켰다. 전처리 전/후의 인식률 비교 실험을 위해 SVM(Support Vector Machines)을 사용하였으며, 학습 데이터 1,409장과 조명 상태를 달리하여 취득한 1,782의 테스트 데이터를 실험 데이터로 사용하였다. 실험 결과, 81.09%라는 성능 향상을 확인하였으며 이는 제안한 전처리 기법이 조명으로 인한 데이터의 상태 변화 문제를 해결해줌으로써 인식 성능 향상에 크게 기여한다는 것을 입증해준다.

• Journal of Convergence for Information Technology
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• 제7권6호
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• pp.229-235
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• 2017

In recent years, research has been actively carried out to recognize and recognize objects based on a large amount of data. In this paper, we propose a system that extracts objects that are thought to be obstacles in road driving images and recognizes them by car, man, and motorcycle. The objects were extracted using Optical Flow in consideration of the direction and size of the moving objects. The extracted objects were recognized using Alexnet, one of CNN (Convolutional Neural Network) recognition models. For the experiment, various images on the road were collected and experimented with black box. The result of the experiment showed that the object extraction accuracy was 92% and the object recognition accuracy was 96%.