• Title/Summary/Keyword: 방향가중치

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An Efficient Separable Weighting Method for Sonar Systems with Non-Separable Planar Arrays (소나시스템 비분리 평면센서배열의 효율적인 분리 가중치 기법)

  • Do, Dae-Won;Kim, Woo-Sik;Lee, Dong-Hun;Kim, Hyung-Moon;Choi, Sang-Moon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.208-217
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    • 2013
  • When a beamforming can be processed separately in horizontal and vertical directions with the planar arrays used in sonar systems, there are several merits such as that practically reduce the required computations and volumes. However, the common planar arrays used in sonar systems are generally non-separable, so the beamforming with separable weighting results in the differences between the desired beam characteristics and the resultant beam characteristics. In this paper, we propose a new separable weighting method which can achieve the wanted beam characteristics by using the separable weights in horizontal and vertical directions for the non-separable planar arrays. In order to achieve the wanted beam characteristics, the proposed method minimizes the differences between the desired weights and the resultant weights based on the number of effective sensors in horizontal and vertical directions of the planar arrays.

Design of Efficient Gradient Orientation Bin and Weight Calculation Circuit for HOG Feature Calculation (HOG 특징 연산에 적용하기 위한 효율적인 기울기 방향 bin 및 가중치 연산 회로 설계)

  • Kim, Soojin;Cho, Kyeongsoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.11
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    • pp.66-72
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    • 2014
  • Histogram of oriented gradient (HOG) feature is widely used in vision-based pedestrian detection. The interpolation is the most important technique in HOG feature calculation to provide high detection rate. In interpolation technique of HOG feature calculation, two nearest orientation bins to gradient orientation for each pixel and the corresponding weights are required. In this paper, therefore, an efficient gradient orientation bin and weight calculation circuit for HOG feature is proposed. In the proposed circuit, pre-calculated values are defined in tables to avoid the operations of tangent function and division, and the size of tables is minimized by utilizing the characteristics of tangent function and weights for each gradient orientation. Pipeline architecture is adopted to the proposed circuit to accelerate the processing speed, and orientation bins and the corresponding weights for each pixel are calculated in two clock cycles by applying efficient coarse and fine search schemes. Since the proposed circuit calculates gradient orientation for each pixel with the interval of $1^{\circ}$ and determines both orientation bins and weights required in interpolation technique, it can be utilized in HOG feature calculation to support interpolation technique to provide high detection rate.

Acceleration of Learning speed Neural Networks by Reducing Weight Oscillations (가중치 진동의 감소를 이용한 신경회로망의 학습속도 향상)

  • 임빈철;박동조
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.251-254
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    • 1998
  • 본 논문에서는 신경회로망의 수렴속도를 높이기 위한 알고리즘을 제안한다. 전형적인 역전파 학습방식은 느린 수렴속도가 단점으로 제기되는데 이는 비용함수의 계곡부근에서 가중치의 궤적이 심한 진동현상을 보이기 때문이다. 이 문제를 해결하기 위해서 본 논문에서는 경사법에서 사용되는 갱신방향을 계곡의 진행방향을 이용하여 변경한다. 모의실험을 통하여 제안된 방법으로 가중치의 궤적에 나타나는 진동을 줄이고 수렴속도를 향상시킬 수 있음을 보인다.

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A Betweenness Centrality Analysis Method in Valued Workflow-supported Social Networks (가중치 워크플로우 소셜 네트워크의 사이중심도 분석방법)

  • Kim, Mee-sun;Kim, Kwang-hoon
    • Journal of Internet Computing and Services
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    • v.17 no.1
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    • pp.65-71
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    • 2016
  • In this paper, we propose a novel analysis method and its algorithms to perform the betweenness centrality measurements on a valued and directed workflow-supported social network. The conventional workflow-supported social network model is to represent the existences of task transferring relationships among their performers by using a binary social network. However, it is necessary to consider not only the existences of task transferring relationships but also their quantities and directions in order to obtain much more effective and sophisticated analysis results. In conclusion, this paper newly defines a concept of valued and directed workflow-supported social network, and its betweenness centrality analysis method and algorithms. Especially, to verify the proposed method and algorithms, we try to apply the conventional method and the proposed method to an example workflow model respectively, and compare their betweenness centrality analysis results.

Fall Recognition Algorithm Using Gravity-Weighted 3-Axis Accelerometer Data (3축 가속도 센서 데이터에 중력 방향 가중치를 사용한 낙상 인식 알고리듬)

  • Kim, Nam Ho;Yu, Yun Seop
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.6
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    • pp.254-259
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    • 2013
  • A newly developed fall recognition algorithm using gravity weighted 3-axis accelerometer data as the input of HMM (Hidden Markov Model) is introduced. Five types of fall feature parameters including the sum vector magnitude(SVM) and a newly-defined gravity-weighted sum vector magnitude(GSVM) are applied to a HMM to evaluate the accuracy of fall recognition. A GSVM parameter shows the best accuracy of falls which is 100% of sensitivity and 97.96% of specificity, and comparing with SVM, the results archive more improved recognition rate, 5.2% of sensitivity and 4.5% of specificity. GSVM shows higher recognition rate than SVM due to expressing falls characteristics well, whereas SVM expresses the only momentum.

Edge-directed demosaicing considering cross channel correlation (채널간 상관관계 및 에지 방향을 고려한 컬러 보간)

  • Yoo, Du-Sic;Kang, Moon-Gi
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.413-414
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    • 2007
  • 본 논문은 칼라 필터 배열(color filter array : CFA) 영상에서 채널 간 상관관계를 이용한 새로운 에지 방향 컬러 보간 방법을 제시하였다. 고정 채널 간 컬러 차 가정에 따라 휘도와 색차간의 차가 큰 경우 에지 영역이라 판단한다. 에지 방향 판별을 정확히 하기 위해 수평, 수직 방향으로 컬러 차 영상을 구하고, 구한 영상에서 변화량을 계산하여 에지 방향 판별 기준으로 사용한다. 에지 판별 기준을 사용하여, 에지 방향에 따라 컬러 보간을 수행한다. 평탄 영역은 이웃 화소와의 유사성에 따라 가중치를 다르게 줘서, 이웃 화소의 가중치 합으로 구한다 실험 결과는 제안하는 알고리즘이 기존 알고리즘 보다 우수함을 보여준다.

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Directional Deinterlacing Method Using Local Gradient Features (국부 Gradient 특징을 이용한 방향성 deinterlacing 방법)

  • Woo, Dong-Hun;Eom, Il-Kyu;Kim, Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.41-46
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    • 2005
  • Deinterlacing is the conversion from interlaced to progressive scan image that is considered to be 2 times image interpolation. In this paper, the simple and effective deinterlacing method is proposed based on the local gradient information of neighborhood pixels. In the proposed method, the weights for directions around the pixel to be interpolated are estimated, and the weighted sum for the neighborhood pixels is the final intensity value of the pixel to be interpolated. The proposed method has the structure suitable to practical implementation and can avoid the artifacts due to the wrong detection of edge direction. In the simulation, it showed improved subjective and objective performance than the ELA method and comparable performance compared with the variation of ELA method which has more complex structure and requires a couple of parameters that is determined by experience.

A Direction Computation and Media Retrieval Method of Moving Object using Weighted Vector Sum (가중치 벡터합을 이용한 이동객체의 방향계산 및 미디어 검색방법)

  • Suh, Chang-Duk;Han, Gi-Tae
    • The KIPS Transactions:PartD
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    • v.15D no.3
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    • pp.399-410
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    • 2008
  • This paper suggests a new retrieval method using weighted vector sum to resolve a problem of traditional location-based retrieval method, nearest neighbor (NN) query, and NN query using direction. The proposed method filters out data with the radius, and then the remained retrieval area is filtered by a direction information compounded of a user's moving direction, a pre-fixed interesting direction, and a pre-fixed retrieval angle. The moving direction is computed from a vector or a weighted vector sum of several vectors using a weight to adopt several cases. The retrieval angle can be set from traditional $360^{\circ}$ to any degree you want. The retrieval data for this method can be a still and moving image recorded shooting location, and also several type of media like text, web, picture offering to customer with location of company or resort. The suggested method guarantees more accurate retrieval than traditional location-based retrieval methods because that the method selects data within the radius and then removes data of useless areas like passed areas or an area of different direction. Moreover, this method is more flexible and includes the direction based NN.

Discovery of Frequent Traversal Patterns on Weighted Graph with Priority (중요도를 고려한 가중치 그래프에서의 빈발 순회패턴 탐사)

  • Lee Seong-Dae;Park Hyu-Chan
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11b
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    • pp.169-171
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    • 2005
  • 그래프를 사용하는 데이터 표현법은 직$\cdot$간접적으로 실세계를 표현하는 다양한 데이터 모델 중에서 가장 일반화된 방법으로 알려져 있다. 기본적으로 그래프는 정점과 간선으로 구성되며, 정점과 간선은 그 중요도나 운영 목적에 따라 다양한 가중치가 부여될 수 있다. 특히, 이러한 그래프를 순회하는 트랜잭션들로부터 중요한 순회패턴을 탐사하는 것은 흥미로운 일이다. 본 논문에서는, 정점과 간선에 가중치가 있고 방향성을 가진 기반 그래프가 주어졌을 때, 그 그래프를 순회하는 트랜잭션들로부터 가중치를 고려하여 빈발 순회패턴을 탐사하는 방법을 제안한다. 또한, 이렇게 탐사한 결과에 가중치를 고려한 중요도를 평가하여 빈발 순회패턴들 간의 우선순위를 결정할 수 있도록 한다. 이 과정에서 발생할 수 있는 트랜잭션 노이즈는 기반 그래프의 간선 가중치의 평균과 표준편차를 이용하여 제거함으로써 보다 신뢰성 있는 빈발 순회패턴을 탐사할 수 있다. 제안한 논문은 웹 로그 마이닝 등 그래프를 이용하는 다양한 응용 분야에 적용할 수 있을 것이다.

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The Edge-Based Motion Vector Processing Based on Variable Weighted Vector Median Filter (에지 기반 가변 가중치 벡터 중앙값 필터를 이용한 움직임 벡터 처리)

  • Park, Ju-Hyun;Kim, Young-Chul;Hong, Sung-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.11C
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    • pp.940-947
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    • 2010
  • Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for high quality display. However, MCFI that directly uses the motion information often suffers from annoying artifacts such as blockiness, ghost effects, and deformed structures. So in this paper, we propose a novel edge-based adaptively weighted vector median filter as post-processing. At first, the proposed method generates an edge direction map through a sobel mask and a weighted maximum frequent filter. And then, outlier MVs are removed by average of angle difference and replaced by a median MV of $3{\times}3$ window. Finally, weighted vector median filter adjusts the weighting values based on edge direction derived from spatial coherence between the edge direction continuity and motion vector. The results show that the performance of PSNR and SSIM are higher up to 0.5 ~ 1 dB and 0.4 ~ 0.8 %, respectively.