• Title/Summary/Keyword: 3D network

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Deep Learning Based Gray Image Generation from 3D LiDAR Reflection Intensity (딥러닝 기반 3차원 라이다의 반사율 세기 신호를 이용한 흑백 영상 생성 기법)

  • Kim, Hyun-Koo;Yoo, Kook-Yeol;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.1
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    • pp.1-9
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    • 2019
  • In this paper, we propose a method of generating a 2D gray image from LiDAR 3D reflection intensity. The proposed method uses the Fully Convolutional Network (FCN) to generate the gray image from 2D reflection intensity which is projected from LiDAR 3D intensity. Both encoder and decoder of FCN are configured with several convolution blocks in the symmetric fashion. Each convolution block consists of a convolution layer with $3{\times}3$ filter, batch normalization layer and activation function. The performance of the proposed method architecture is empirically evaluated by varying depths of convolution blocks. The well-known KITTI data set for various scenarios is used for training and performance evaluation. The simulation results show that the proposed method produces the improvements of 8.56 dB in peak signal-to-noise ratio and 0.33 in structural similarity index measure compared with conventional interpolation methods such as inverse distance weighted and nearest neighbor. The proposed method can be possibly used as an assistance tool in the night-time driving system for autonomous vehicles.

Implementation of a Window-Masking Method and the Soft-core Processor based TDD Switching Control SoC FPGA System (윈도 마스킹 기법과 Soft-core Processor 기반 TDD 스위칭 제어 SoC 시스템 FPGA 구현)

  • Hee-Jin Yang;Jeung-Sub Lee;Han-Sle Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.3
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    • pp.166-175
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    • 2024
  • In this paper, the Window-Masking Method and HAT (Hardware Attached Top) CPU SoM (System on Module) are used to improve the performance and reduce the weight of the MANET (Mobile Ad-hoc Network) network synchronization system using time division redundancy. We propose converting it into a RISC-V based soft-core MCU and mounting it on an FPGA, a hardware accelerator. It was also verified through experiment. In terms of performance, by applying the proposed technique, the synchronization acquisition range is from -50dBm to +10dBm to -60dBm to +10dBm, the lowest input level for synchronization is increased by 20% from -50dBm to -60dBm, and the detection delay (Latency) is 220ns. Reduced by 43% to 125ns. In terms of weight reduction, computing resources (48%), size (33%), and weight (27%) were reduced by an average of 36% by replacing with soft-core MCU.

ISDN Experimental Experiences on User-Network Interfaces (ISDN 가입자 - 망 접속에서의 실험적 경험에 대한 고찰)

  • Jeong, Il-Yeong;Jeong, Hui-Chang;Jo, Gyu-Seop;Im, Ju-Hwan
    • ETRI Journal
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    • v.10 no.1
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    • pp.3-13
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    • 1988
  • With the contunuing trends towards an information based society, telecommunications services are becoming an integral part of social activities. So, emphasis on ISDN is growing rapidly and placed on supporting integrated services delivery of different levels to the end user. The end user’s perception of an integraged services delivery(in particular, ISDN services) should reflect three interrelated capabilities, ISDN access capabilities and ISDN network capabilities. For turning the ISDN concept of above capabilities into reality, we have implemented the experimental system on user-network interfaces, which are three kinds of implementations in user access arrangements, namely basic access, intermediate rate multiplexed access and primary rate multiplexed access. Through these implementations, NTE(Network Terminating Equipment) is used for single basic access [2B+D], IMUX (Intermediate rate Multiplexer) for 4 basic accesses [4X(2B+D)] and PMUX(Primary rate Multiplexer) for [10/12 X (2B+D)]. This paper describes the outlines of system features on user access equipments, system architectures of testbed and experiment result of each access arrangements.

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Trends of 3D R&D Policy in Japan (일본의 3D 연구개발 정책동향)

  • Kim, P.R.
    • Electronics and Telecommunications Trends
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    • v.27 no.2
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    • pp.149-157
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    • 2012
  • 최근까지 정체 국면에 있던 3D 산업이 2012년부터는 런던 올림픽과 여수 EXPO 등 글로벌 이벤트 발생으로 관련 산업이 활성화될 것으로 전망되고 있다. BBC 등 글로벌 미디어들도 3D 방송을 본격화할 예정이어서 3D 콘텐츠 시장이 국내외적으로 급성장할 것으로 기대된다. 우리나라는 아직까지 3D 산업이 초기 시장이기 때문에 향후 3D 산업을 육성 발전시키기 위해서는 정부의 역할이 중요하다고 할 수 있다. 본고의 목적은 정부 주도로 연구개발을 수행하면서 3D 연구개발 분야에서 세계를 선도하고 있는 일본의 3D 연구개발 정책동향을 살펴보고, 우리나라에 주는 시사점을 발굴하는 것이다. 이러한 목적을 달성하기 위하여 본고에서는 'UNS(Universal Communications, New Generation Networks, Security and Safety for the Ubiquitous Network Society) 전략 프로그램 II'를 중심으로 일본의 3D 기술개발 관련 주요 전략을 살펴 보았으며, 3D 기술개발을 위한 R&D 조직인 NICT(National Institute of Information and Communication Technology) 및 URCF(Ultra-Realistic Communications Forum)의 역할을 소개하는 한편, 일본의 3차원 영상기술에 의한 초현장감 커뮤니케이션 기술개발의 현황과 전망을 고찰하였다.

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Self Organization of Sensor Networks for Energy-Efficient Border Coverage

  • Watfa, Mohamed K.;Commuri, Sesh
    • Journal of Communications and Networks
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    • v.11 no.1
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    • pp.57-71
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    • 2009
  • Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications.

stereo vision for monochromatic surface recognition based on competitive and cooperative neural network

  • Kang, Hyun-Deok;Jo, Kang-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.41.2-41
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    • 2002
  • The stereo correspondence of two retinal images is one of the most difficult problems in stereo vision because the reconstruction of 3-D scene is a typical visual ill-posed problem. So far there still have been many unsolved problems, one of which is to reconstruct 3-D scene for a monochromatic surface because there is no clue to make a correspondence between two retinal images. We consider this problem with two layered self-organization neural network to simulate the competitive and cooperative interaction of binocular neurons. A...

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UV Mapping Based Pose Estimation of Furniture Parts in Assembly Manuals (UV-map 기반의 신경망 학습을 이용한 조립 설명서에서의 부품의 자세 추정)

  • Kang, Isaac;Cho, Nam Ik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.07a
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    • pp.667-670
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    • 2020
  • 최근에는 증강현실, 로봇공학 등의 분야에서 객체의 위치 검출 이외에도, 객체의 자세에 대한 추정이 요구되고 있다. 객체의 자세 정보가 포함된 데이터셋은 위치 정보만 포함된 데이터셋에 비하여 상대적으로 매우 적기 때문에 인공 신경망 구조를 활용하기 어려운 측면이 있으나, 최근에 들어서는 기계학습 기반의 자세 추정 알고리즘들이 여럿 등장하고 있다. 본 논문에서는 이 가운데 Dense 6d Pose Object detector (DPOD) [11]의 구조를 기반으로 하여 가구의 조립 설명서에 그려진 가구 부품들의 자세를 추정하고자 한다. DPOD [11]는 입력으로 RGB 영상을 받으며, 해당 영상에서 자세를 추정하고자 하는 객체의 영역에 해당하는 픽셀들을 추정하고, 객체의 영역에 해당되는 각 픽셀에서 해당 객체의 3D 모델의 UV map 값을 추정한다. 이렇게 픽셀 개수만큼의 2D - 3D 대응이 생성된 이후에는, RANSAC과 PnP 알고리즘을 통해 RGB 영상에서의 객체와 객체의 3D 모델 간의 변환 관계 행렬이 구해지게 된다. 본 논문에서는 사전에 정해진 24개의 자세 후보들을 기반으로 가구 부품의 3D 모델을 2D에 투영한 RGB 영상들로 인공 신경망을 학습하였으며, 평가 시에는 실제 조립 설명서에서의 가구 부품의 자세를 추정하였다. 실험 결과 IKEA의 Stefan 의자 조립 설명서에 대하여 100%의 ADD score를 얻었으며, 추정 자세가 자세 후보군 중 정답 자세에 가장 근접한 경우를 정답으로 평가했을 때 100%의 정답률을 얻었다. 제안하는 신경망을 사용하였을 때, 가구 조립 설명서에서 가구 부품의 위치를 찾는 객체 검출기(object detection network)와, 각 개체의 종류를 구분하는 객체 리트리벌 네트워크(retrieval network)를 함께 사용하여 최종적으로 가구 부품의 자세를 추정할 수 있다.

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Thermal Analysis of Water Cooled ISG Based on a Thermal Equivalent Circuit Network

  • Kim, Kyu-Seob;Lee, Byeong-Hwa;Jung, Jae-Woo;Hong, Jung-Pyo
    • Journal of Electrical Engineering and Technology
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    • v.9 no.3
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    • pp.893-898
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    • 2014
  • Recently, the interior permanent synchronous motor (IPMSM) has been applied to an integrated starter and generator (ISG) for hybrid electric vehicles. In the design of such a motor, thermal analysis is necessary to maximize the power density because the loss is proportional to the power of a motor. Therefore, a cooling device as a heat sink is required internally. Generally, a cooling system designed with a water jacket structure is widely used for electric motors because it has advantages of simple structure and cooling effectiveness. An effective approach to analyze an electric machine with a water jacket is a thermal equivalent network. This network is composed of thermal resistance, a heat source, and thermal capacitance that consider the conduction, convection, and radiation. In particular, modeling of the cooling channel in a network is challenging owing to the flow of the coolant. In this paper, temperature prediction using a thermal equivalent network is performed in an ISG that has a water cooled system. Then, an experiment is conducted to verify the thermal equivalent network.

A Proposal of Shuffle Graph Convolutional Network for Skeleton-based Action Recognition

  • Jang, Sungjun;Bae, Han Byeol;Lee, HeanSung;Lee, Sangyoun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.4
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    • pp.314-322
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    • 2021
  • Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

Analysis of flow through dam foundation by FEM and ANN models Case study: Shahid Abbaspour Dam

  • Shahrbanouzadeh, Mehrdad;Barani, Gholam Abbas;Shojaee, Saeed
    • Geomechanics and Engineering
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    • v.9 no.4
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    • pp.465-481
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    • 2015
  • Three-dimensional simulation of flow through dam foundation is performed using finite element (Seep3D model) and artificial neural network (ANN) models. The governing and discretized equation for seepage is obtained using the Galerkin method in heterogeneous and anisotropic porous media. The ANN is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning, using the water level elevations of the upstream and downstream of the dam, as input variables and the piezometric heads as the target outputs. The obtained results are compared with the piezometric data of Shahid Abbaspour's Dam. Both calculated data show a good agreement with available measurements that demonstrate the effectiveness and accuracy of purposed methods.