• 제목/요약/키워드: Spatial gradient

검색결과 329건 처리시간 0.027초

JPEG-2000 Gradient-Based Coding: An Application To Object Detection

  • Lee, Dae Yeol;Pinto, Guilherme O.;Hemami, Sheila S.
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2013년도 추계학술대회
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    • pp.165-168
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    • 2013
  • Image distortions, such as quantization errors, can have a severe negative impact on the performance of computer vision algorithms, and, more specifically, on object detection algorithms. State-of-the-art implementations of the JPEG-2000 image coder commonly allocate the available bits to minimize the Mean-Squared-Error (MSE) distortion between the original image and the resulting compressed image. However, considering that some state-of-the-art object detection methods use the gradient information as the main image feature, an improved object detection performance is expected for JPEG-2000 image coders that allocate the available bits to minimize the distortions on the gradient content. Accordingly, in this work, the Gradient Mean-Squared-Error (GMSE) based JPEG-2000 coder presents an improved object detection performance over the MSE based JPEG-2000 image coder when the object of interest is located at the same spatial location of the image regions with the strongest gradients and also for high bit-rates. For low bit-rates (e.g. 0.07bpp), the GMSE based JPEG-2000 image coder becomes overly selective in choosing the gradients to preserve, and, as a result, there is a greater chance of mismatch between the spatial locations of the gradients that the coder is trying to preserve and the spatial locations of the objects of interest.

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Ionospheric Storm and Spatial Gradient Analysis for GBAS

  • Kim, Jeong-Rae;Yang, Tae-Hyoung;Lee, Young-Jae;Jun, Hyang-Sig;Nam, Gi-Wook
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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    • pp.361-365
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    • 2006
  • High ionospheric spatial gradient during ionospheric storm is most concern for the landing approach with GNSS (Global Navigation Satellite System) augmentation systems. In case of the GBAS (Ground-Based Augmentation System), the ionospheric storm causes sudden increase of the ionospheric delay difference between a ground facility and a user (aircraft), and the aircraft position error increases significantly. Since the ionosphere behavior and the storm effect depend on geographic location, understanding the ionospheric storm behavior at specific regional area is crucial for the GNSS augmentation system development and implementation. Korea Aerospace Research Institute and collaborating universities have been developing an integrity monitoring test bed for GBAS research and for future regional augmentation system development. By using the dense GPS (Global Positioning System) networks in Korea, a regional ionosphere map is constructed for finding detailed aspect of the ionosphere variation. Preliminary analysis on the ionospheric gradient variation during a recent storm period is performed and the results are discussed.

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Autonomous Drone Path Planning for Environment Sensing

  • Kim, Beomsoo;Lee, Sooyong
    • 센서학회지
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    • 제27권4호
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    • pp.209-215
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    • 2018
  • Recent research in animal behavior has shown that gradient information plays an important role in finding food and home. It is also important in optimization of performance because it indicates how the inputs should be adjusted for maximization/minimization of a performance index. We introduce perturbation as an additional input to obtain gradient information. Unlike the typical approach of calculating the gradient from the derivative, the proposed processing is very robust to noise since it is performed as a summation. Experimental results prove the validity of the process of spatial gradient acquisition. Quantitative indices for measuring the effect of the amplitude and the frequency are developed based on linear regression analysis. Drones are very useful for environmental monitoring and an autonomous path planning is required for unstructured environment. Guiding the drone for finding the origin of the interested physical property is done by estimating the gradient of the sensed value and generating the drone trajectories in the direction which maximizes the sensed value. Simulation results show that the proposed method can be successfully applied to identify the source of the physical quantity of interest by utilizing it for path planning of an autonomous drone in 3D environment.

GPS 주파수간 편이 추정정확도 분석 (Estimation Accuracy Analysis of GPS Inter-Frequency Biases)

  • 김민우;김정래;허문범
    • 항공우주시스템공학회지
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    • 제4권1호
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    • pp.19-22
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    • 2010
  • The accuracy and integrity of global navigation satellite systems (GNSS) can be improved by using GNSS augmentation systems. Large ionospheric spatial gradient, during ionosphere storm, is a major threat for using GNSS augmentation systems by increasing the spatial decorrelation between a reference system and users. Ionosphere decorrelation behavior can be analyzed by using dual frequency GPS data. GNSS receivers have their own biases, called inter-frequency bias (IFB) between dual(P1 and P2) frequencies and they must be accurately estimated before computing ionosphere delays. GPS network data in Korea is used to compute each receiver's IFB, and their estimation accuracy and variability are analyzed. IFB estimation methodology to apply for ionosphere gradient analysis is discussed.

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Dynamic Caching Routing Strategy for LEO Satellite Nodes Based on Gradient Boosting Regression Tree

  • Yang Yang;Shengbo Hu;Guiju Lu
    • Journal of Information Processing Systems
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    • 제20권1호
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    • pp.131-147
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    • 2024
  • A routing strategy based on traffic prediction and dynamic cache allocation for satellite nodes is proposed to address the issues of high propagation delay and overall delay of inter-satellite and satellite-to-ground links in low Earth orbit (LEO) satellite systems. The spatial and temporal correlations of satellite network traffic were analyzed, and the relevant traffic through the target satellite was extracted as raw input for traffic prediction. An improved gradient boosting regression tree algorithm was used for traffic prediction. Based on the traffic prediction results, a dynamic cache allocation routing strategy is proposed. The satellite nodes periodically monitor the traffic load on inter-satellite links (ISLs) and dynamically allocate cache resources for each ISL with neighboring nodes. Simulation results demonstrate that the proposed routing strategy effectively reduces packet loss rate and average end-to-end delay and improves the distribution of services across the entire network.

개방형 자기공명영상시스템을 위한 평면형 경사자계코일 (Planar Gradient Coils for an Open MRI System)

  • 이수열;박부식;이정한;이완
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1996년도 추계학술대회
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    • pp.165-168
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    • 1996
  • Though the planar gradient coils, designed by the magnetic energy minimization procedure, have smaller inductance than conventional gradient coils, the planar gradient oils often suffer from their poor magnetic field linearity. Scaling the spatial frequencies of the current density function designed by the magnetic energy minimization procedure, magnetic field linearity of the planar gradient coils can be featly improved with small sacrifice of gradient coil inductance.

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3D 공간상에서의 주변 기울기 정보를 기반에 둔 필터 학습을 통한 MRI 영상 초해상화 (MRI Image Super Resolution through Filter Learning Based on Surrounding Gradient Information in 3D Space)

  • 박성수;김윤수;감진규
    • 한국멀티미디어학회논문지
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    • 제24권2호
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    • pp.178-185
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    • 2021
  • Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

소재 크기효과를 고려한 미세가공공정 유한요소해석 (Finite Element Analysis for Micro-Forming Process Considering the Size Effect of Materials)

  • 변상민;이영석
    • 소성∙가공
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    • 제15권8호
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    • pp.544-549
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    • 2006
  • In this work, we have employed the strain gradient plasticity theory to investigate the effect of material size on the deformation behavior in metal forming process. Flow stress is expressed in terms of strain, strain gradient (spatial derivative of strain) and intrinsic material length. The least square method coupled with strain gradient plasticity was used to calculate the components of strain gradient at each element of material. For demonstrating the size effect, the proposed approach has been applied to plane compression process and micro rolling process. Results show when the characteristic length of the material comes to the intrinsic material length, the effect of strain gradient is noteworthy. For the microcompression, the additional work hardening at higher strain gradient regions results in uniform distribution of strain. In the case of micro-rolling, the strain gradient is remarkable at the exit section where the actual reduction of the rolling finishes and subsequently strong work hardening take places at the section. This results in a considerable increase in rolling force. Rolling force with the strain gradient plasticity considered in analysis increases by 20% compared to that with conventional plasticity theory.

모션 그래디언트 히스토그램 기반의 시공간 크기 변화에 강인한 동작 인식 (Spatial-Temporal Scale-Invariant Human Action Recognition using Motion Gradient Histogram)

  • 김광수;김태형;곽수영;변혜란
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권12호
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    • pp.1075-1082
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    • 2007
  • 본 논문은 동영상에 등장하는 다수 사람의 동작을 검출하여 검출된 동작을 개별적으로 인식하는 방법을 제안한다. 동작이 수행되는 속도 또는 크기 변화에 강인한 인식 성능을 갖기 위해 시공간축 피라미드(Spatial-Temporal Pyramid)방식을 적용한다. 동작 표현 방식을 통계적 특성 기반의 모션 그래디언트 히스토그램(MGH:Motion Gradient Histogram)으로 선택하여 인식 과정에서 발생하는 복잡도를 최소화 하였다. 다수의 동작을 검출하기 위하여 이진 차영상을 축적한 모션 에너지 이미지(MEI: Motion Energy Image) 방법을 적용하여 효율적으로 개별적 동작 영역을 획득한다. 각 영역은 동작 표현 방법인 MGH로 나타내어지고, 크기 변화에 강인하도록 피라미드 방식을 적응하여 학습된 템플릿 MGH와 유사도를 상호 비교하여 최종 인식 결과를 얻는다. 인식 성능의 평가를 위해 10개의 동영상을 활용하여 단일 객체, 다수 객체, 속도 및 크기 변화, 기존 방식과의 비교, 기타 추가 실험 등을 실시하여 다양한 조건의 영상에서 양호한 인식 결과를 확인 할 수 있었다.

부분적인 경사자계를 이용한 고속 자기공명 영상촬영기법 (Fast MR Imaging Technique by Using Locally-Linear Gradient Field)

  • 양윤정;이종권
    • 대한의용생체공학회:의공학회지
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    • 제17권1호
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    • pp.93-98
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    • 1996
  • The purpose of this paper is to propose a new localized imaging method of reduced imaging time luting a locally-linear gradient. Since most fast MR(Magnetic Resonance) imaging methods need the whole $\kappa$-space(Spatial frequency space) data corresponding to the whole imaging area, there are limitstions in reducing the minimum imaging time. The imaging method proposed in this paper uses a specially-made gradient coil generating a local ramp-shape field and uniform field outside of the imaging areal Conventional imaging sequences can be used without any RF/gradient pulse sequence modifiestions except the change in the number of encoding steps and the field of view.

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