• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.552-557
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• 2000

In the paper, we proposed a face recognition method that uses GA-BP(Genetic Algorithm-Back propagation Network) that optimizes initial parameters such as bias values or weights. Each pixel in the picture is used for input of the neuralnetwork. The initial weights of neural network is consist of fixed-point real values and converted to bit string on purpose of using the individuals that arte expressed in the Genetic Algorithm. For the fitness value, we defined the value that shows the lowest error of neural network, which is evaluated using newly defined adaptive re-learning operator and built the optimized and most advanced neural network. Then we made experiments on the face recognition. In comparison with learning convergence speed, the proposed algorithm shows faster convergence speed than solo executed back propagation algorithm and provides better performance, about 2.9% in proposed method than solo executed back propagation algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.425-428
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• 2002

본 논문에서는 한 장의 정면 얼굴 영상만으로 회전 변형을 수행할 수 있는 새로운 영상기반렌더링(Image Based Rendering, IBR) 기법을 제안한다. 3차원 기하학적 모델을 대신하면서 수평 회전 변형을 연출하기 위해, 특정 인물의 정면, 좌우 반측면, 좌우 측면의 얼굴 영상에 대한 표준 메쉬 집합을 작성한다. 변형하고자 하는 임의의 인물에 대해서는 정면 영상에 대한 메쉬만을 작성하고, 나머지 측면 참조 메쉬들은 표준 메쉬 집합에 의해 자동으로 생성된다. 입체적인 회전 효과를 연출하기 위해, 회전 변형시 발생할 수 있는 제어점들간의 중첩 및 역전을 허용하도록 기존의 두 단계 메쉬워프 알고리즘을 개선한 역전가능 메쉬워프 알고리즘(invertible meshwarp algorithm)을 제안한다. 이 알고리즘을 이용하여 다양한 남녀노소의 정면 얼굴 영상에 대해 회전에 따른 포즈 변형을 수행하여 비교적 자연스러운 포즈 변형 결과를 얻었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1032-1037
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• 2006

The channel is one of the precious and limited resources in wireless networks. There are many researches on the channel management. Recently, the optimization problem of guard channels has been an important issue. In this paper, we propose an intelligent channel management technique based on the neural networks. An SRN channel allocation model is developed to generate the learning data for the neural networks and the performance analysis of system. In the proposed technique, the neural network is trained to generate optimal guard channel number g, using backpropagation supervised learning algorithm. The optimal g is computed using the neural network and compared to the g computed by the SRM model. The numerical results show that the difference between the value of 8 by backpropagation and that value by SRM model is ignorable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.119-125
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• 2019

Recently, it has become a social problem due to fine particles. There are more people wearing masks, weather alerts and disaster notices. Research and policy are actively underway. Meteorologically, the biggest damage caused by fine particles is the inversion layer phenomenon. In this study, we designed a system to warn fine Particles by analyzing inversion layer and wind direction. This weather information system proposes a system that can efficiently perform scalability and parallel processing by using OGC sensor web enablement system and NoSQL storage for sensor control and data exchange.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.2
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• pp.13-22
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• 2005

To improve the anomaly IDS using system calls, this study focuses on Neural Networks Learning using the Soundex algorithm which is designed to change feature selection and variable length data into a fixed length learning pattern. That is, by changing variable length sequential system call data into a fixed length behavior pattern using the Soundex algorithm, this study conducted neural networks learning by using a backpropagation algorithm with fuzzy membership function. The back-propagation neural networks and Neuro-Fuzzy technique are applied for anomaly intrusion detection of system calls using Sendmail Data of UNM to demonstrate its aspect of he complexity of time, space and MDL performance.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.153-163
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• 2003

In this paper, we propose a new technique of image based rendering(IBR) for the pose transformation of a face by using only a frontal face image and its mesh without a three-dimensional model. To substitute the 3D geometric model, first, we make up a standard mesh set of a certain person for several face sides ; front. left, right, half-left and half-right sides. For the given person, we compose only the frontal mesh of the frontal face image to be transformed. The other mesh is automatically generated based on the standard mesh set. And then, the frontal face image is geometrically transformed to give different view by using Invertible Meshwarp Algorithm, which is improved to tolerate the overlap or inversion of neighbor vertexes in the mesh. The same warping algorithm is used to generate the opening or closing effect of both eyes and a mouth. To evaluate the transformation performance, we capture dynamic images from 10 persons rotating their heads horizontally. And we measure the location error of 14 main features between the corresponding original and transformed facial images. That is, the average difference is calculated between the distances from the center of both eyes to each feature point for the corresponding original and transformed images. As a result, the average error in feature location is about 7.0% of the distance from the center of both eyes to the center of a mouth.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.463-472
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• 2009

Real-time operating systems must have satisfying various conditions such as effective scheduling policies, minimized interrupt delay, resolved priority inversion problems, and its applications to be completed within desired deadline. The real-time operating systems, therefore, should be designed and developed to be optimal for these requirements. MicroC/OS-II, a kind of Real-time operating systems, uses the basic priority inheritance with a mutex to solve priority inversion problems. For the implementation of mutex, the kernel in an operating system should provide supports for numerous tasks with same priority. However, MicroC/OS-II does not provide this support for the numerous tasks of same priority. To solve this problem, MicroC/OS-II cannot but using priority reservation, which leads to the waste of unnecessary resources. In this study, we have dealt with new design a protocol, so called TPSP(Temporary Priority Swap Protocol), by an effective solution for above-mentioned problem, eventually enabling embedded systems with constrained resources environments to run applications.

• The Journal of Information Technology
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• v.8 no.1
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• pp.51-56
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• 2005

The Back propagation algorithm is a very effective supervised training method for multi-layer feed forward neural networks. This paper studies the decision boundary formation based on the Back propagation algorithm. The discriminating powers of several neural network topology are also investigated against five manually created data sets. It is found that neural networks with multiple hidden layer perform better than single hidden layer.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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• pp.691-693
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• 1998

A parallel processing systolic array reduces execution time of the Back-propagation ANN. But, systolic array must be designed whenever the number of neurons in the ANN differ. To use the systolic array which is aready designed ad a fixed size VLSI chip, partition of the problem size systolic array must be performed. This paper presents a design method of the fixed size systolic array for the Back-propagation algorthm using LSGP and LPGS partion method

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.398-400
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• 1999

본 논문에서는 저항 생산 과정에서 실제저항값과 칼라 코드값이 잘못 표기되는 경우에 이를 검사.인식하는 시스템에 이용할 수 있는 알고리즘을 제안한다. 본 알고리즘에서는 칼라 영상에서의 효과적인 경계선 추출 방법과 칼라 영상의 명암도 변화 차이를 이용한 저항의 칼라 코드 영역 추출법, 그리고 역전파 알고리즘을 이용한 칼라 코드 판별법이 제시된다.