• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1340-1345
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• 2001

In this paper, we proposed the method computing the optimal solution of Optical Flow(OF) representing the moving information of moving object and improving the operating speed. In order to do that, we computed the optimal solution of OF using the Combinatorial Hough Transform(CHT) and Voting accumulation and simply searched the moving object compared to conventional method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.420-423
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• 1998

최근 이동 통신이나 위성통신과 같은 많은 디지털 통신 시스템에서 시스템의 용량을 증가시키고 인접 채널간 간섭을 줄이기 위해 많은 연구가 진행되고 있으며, 그 중에서 어레이 빔 형성 기법에 대한 연구가 활발하게 진행되고 있다. 이에 본 논문에서는 원하는 신호의 입사방향을 모르더라도 정상 동작이 가능한 블라인드 빔 형성 기법 중에서 신호의 cyclostationarity를 이용한 방법을 사용하여 원하는 사용자 신호의 cyclic 주파수만큼 천이된 신호와 수신신호 사이의 상호상관 행렬을 구하고 이를 이용하여 계수벡터를 구하는 알고리즘을 제시한다.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1410-1412
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• 1999

Protective relay for transformer operates in general by comparing with the differential current and the restraint current. These kinds of currents are changed on magnitude and phasor during the fault according to winding type and vector group. This paper presents the differential and restraint currents and operational principle of differential protective relay for two-winding and three-winding transformer with graphical model. It is developed using MATLAB for an educational purpose on engineer related in power system and protection in university and power utility including large factory.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1903-1904
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• 2008

이 논문에서는 영상 프레임사이의 움직임 벡터 연구에 기반을 둔 빠른 블록 정합 움직임 추정을 위해 보완된 다이아몬드 탐색 알고리즘을 제안한다. 실험 결과는 제안된 알고리즘이 기존의 다이아몬드 탐색 알고리즘 보다 더 적은 탐색으로 좀 더 빠르게 동작하는 것이 가능하다. 본 알고리즘의 특징은 움직임이 적은 블록에 대해서는 CDS(conjugate direction search) 알고리즘을 적용하여 탐색함으로써 탐색 점의 수를 줄일 수 있어 좀 더 빠르게 움직임 추정을 할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.574-576
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• 2007

판례 자동분류 시스템은 일반적인 문서 자동분류 시스템과 기본적인 동작방법은 동일하다. 본 논문에서는 노동법에 관련된 판례를 대상으로 지지벡터기계(SVM), 단일 의사결정나무, 복수 의사결정나무, 신경망 기법 등을 사용하여 문서의 자동 분류 실험을 수행하고, 판례분류에 가장 적합한 기계학습기법이 무엇인지를 실험해 보았다. 실험 결과 복수 의사결정나무가 93%로 가장 높은 정확도를 나타내었다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.508-514
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• 2018

An electroencephalogram (EEG) evaluates the electrical activity generated by brain cell interactions that occur during brain activity, and an EEG can evaluate the brain activity caused by hand movement. In this study, a 16-channel EEG was used to measure the EEG generated before and after hand movement. The measured data can be classified as a supervised learning model, a support vector machine (SVM). To shorten the learning time of the SVM, a feature extraction and vector dimension reduction by filtering is proposed that minimizes motion-related information loss and compresses EEG information. The classification results showed an average of 72.7% accuracy between the sitting position and the hand movement at the electrodes of the frontal lobe.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.124-129
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• 2013

This paper proposes a high-performance vector inner product calculation circuit for real-time object recognition based on SVM algorithm. SVM algorithm shows a higher detection rate than other object recognition algorithms. However, it requires a huge amount of computational efforts. Since vector inner product calculation is one of the major operations of SVM algorithm, it is important to implement a high-performance vector inner product calculation circuit for real-time object recognition capability. The proposed circuit adopts the pipeline architecture with six stages to increase the operating speed and makes it possible to recognize objects in real time based on SVM. The proposed circuit was described in Verilog HDL at RTL. For silicon verification, an MPW chip was fabricated using TSMC 180nm standard cell library. The operation of the implemented MPW chip was verified on the test board with test application software developed for the chip verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.1
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• pp.17-22
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• 2013

If we were in a head-on or crossing situation with a target ship and did not know the target ship's intention to change her course, we might be confused about our decision making to change our course for collision avoidance and be in a danger of collision. In order to solve these problems, we need to develop an automatic system which enables mariners to easily detect a change in the target ship's course and efficiently avoid being on a collision course. In this paper, we proposed an early detection method on altering course of a target ship using the steering wheel signal. This method will contribute to the reduction of collision accidents and also be used to the VTS system and the analysis of marine accidents.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.718-727
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• 2022

The Korean domestic cartoon industry has grown explosively by 65% compared to the previous year. Then the market size is expected to exceed KRW 1 trillion. However, excessive work results in health deterioration. Moreover, this working environment makes the production of human resources insufficient, repeating a vicious cycle. Although some tasks require creation activity during cartoon production, there are still a lot of simple repetitive tasks. Therefore, this study aimed to develop a method for creating a character pose through human pose estimation (HPE). The HPE is to detect key points for each joint of a user. The primary role of the proposed method was to make each joint of the character match that of the human. The proposed method enabled us to create the pose of the two-dimensional cartoon character through the results. Furthermore, it was possible to save the static image for one character pose and the video for continuous character pose.