• Tunnel and Underground Space
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• v.6 no.4
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• pp.316-325
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• 1996

A new accelerated neural network adopting modified sigmoid function was developed and applied to estimate engineering properties of rock from insufficient geological data. Developed network was tested on the well-known XOR and character recognition problems to verify the validity of the algorithms. Both learning speed and recognition rate were improved. Test learn on the Lee and Sterling's problems showed that learning time was reduced from tens of hours to a few minutes, while the output pattern was almost the same as other studies. Application to the various case studies showed exact coincidence with original data or measured results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.1
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• pp.18-26
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• 1988

In this paper, it is presented a procedure to recognize hand-written Korean characters by syntax analysis to the graph pattern using the context-free attributed grammers. Using this algorithm rexognition tests have been made for the 384 characters written by three persons, and have obtained 93% of correct recognition rate in average.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.293-297
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• 1992

For the computerized monitoring and diagnosis of the undesirable chip chatter which are major obstacles to FMS, a pattern recognition system based on multi-layer perception neural network is developed and the performance of the system is experimentally evaluated. Experimental results show that recognition of the two class state of normal or abnormal cutting gives satisfactory results with success rate of 81`91%. Therefore, the proposed system has possibility for use in monitoring and diagnosis of automatic manufacturing system

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.189-190
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• 2017

인공망막의 효율성을 높이기 위해 생물학적 인간의 시각정보과정에 여러 연구가 진행 중이다. 인간의 시각정보처리과정에는 시각정보를 축약하는 특성을 가지고 있다. 본 논문에서는 인간의 시각체계를 기반으로 영상 자체를 인식하지 않고 정보를 압축한 후 복원된 영상에 대한 인식 모델을 제안하고자 한다. 실험결과, 제안된 인식 모델과 일반적 인식모델과의 차이가 없음을 알 수 있었다.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.671-674
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• 1988

This paper describes a matching method to solve the problem of occlusion in a two dimensional scene. The technique consist of three steps: generation of hypotheses, clustering of hypotheses by matching probability, updating of hypotheses. Using this algorithm, simulation results have been tested for 20 scenes contained the 80 models, and have obtained 95% of properly correct recognition rate in average.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.150-154
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• 2003

The distortion effects of microphones have been analyzed and compensated at mel-frequency feature domain. Unlike popular bias removal algorithms a linear transformation of mel-frequency spectrum is incorporated. Although a diagonal matrix transformation is sufficient for medium-quality microphones, a full-matrix transform is required for low-quality microphones with severe nonlinearity. Proposed compensation algorithms are tested with HTIMIT database, which resulted in about 5 percents improvements in recognition rate over conventional CMS algorithm.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.1017-1018
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• 2006

We measured EEG, extracted the feature vectors using alpha and beta rhythm from the measured EEG and pattern recognition was simulated by using the feature vector and the algorithms which are conventional LVQ and Forward only Counter Propagation Networks. And then the successful rate of pattern class of EEG data had about 76 %.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.395-396
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• 2019

최근 컴퓨터 하드웨어, 소프트웨어의 급속한 발전으로 상용화되면서 생체 인식 기술은 몇 년 전부터 점차 넓은 시장을 형성하고 있다. 본 논문에서는 얼굴 인식을 위하여 학습 데이터구성과 특징데이터에 따른 인식 정도를 파악하고 효과적인 방법으로 학습할 수 있는 방법을 제안하고자 한다. 실험결과, 원영상 그대로 인식하는 것 보다 특징 데이터를 구성하여 학습하는 것이 효율적임을 알 수 있다.

• Journal of KIISE:Software and Applications
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• v.33 no.1
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• pp.130-137
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• 2006

The depth information in the face represents personal features in detail. In particular, the surface curvatures extracted from the face contain the most important personal facial information. This surface curvature and together with grouped projection vector which reduces the dimensions resulting less computations are collaborated into the proposed 3D face recognition algorithm. The maximum and minimum curvature are calculated from the surface curvature image, which are grouped into projected vectors for recognition. The minimum curvature showed the best recognition rate among the surface parameters.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.223-228
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• 2016

A digital micromirror system was proposed for future smart learning. This system is the compact micro-projector with a built-in CMOS sensor modules. It can provide the various interfaces. The basis of interface is to recognize the finger tip on projected image. But the recognition rate of finger tip is very low due to various image degradations. In this paper, we propose the finger tip recognition algorithm that minimize the image degradation factors by using the Retinex transform and IR structuring light. By verifying the availability of the algorithm through experiment, the performance of finger tip recognition was confirmed. Therefore, the user interface can be able to be enhanced significantly in DMS.