• Title/Summary/Keyword: object based structure

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3D Nano Object Recognition based on Phase Measurement Technique

  • Kim, Dae-Suk;Baek, Byung-Joon;Kim, Young-Dong;Javidi, Bahram
    • Journal of the Optical Society of Korea
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    • v.11 no.3
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    • pp.108-112
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    • 2007
  • Spectroscopic ellipsometry (SE) has become an important tool in scatterometry based nano-structure 3D profiling. In this paper, we propose a novel 3D nano object recognition method by use of phase sensitive scatterometry. We claims that only phase sensitive scatterometry can provide a reasonable 3D nano-object recognition capability since phase data gives much higher sensitive 3D information than amplitude data. To show the validity of this approach, first we generate various $0^{th}$ order SE spectrum data ($\psi$ and ${\Delta}$) which can be calculated through rigorous coupled-wave analysis (RCWA) algorithm and then we calculate correlation values between a reference spectrum and an object spectrum which is varied for several different object 3D shape.

LSTM Network with Tracking Association for Multi-Object Tracking

  • Farhodov, Xurshedjon;Moon, Kwang-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.23 no.10
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    • pp.1236-1249
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    • 2020
  • In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

Index Structure and Trajectory Data Generation Algorithm to Process the Trajectory of Moving Object (이동 객체의 궤적 처리를 위한 색인 구조 및 궤적 데이터 생성 알고리즘)

  • Chae, Cheol-Joo;Kim, Yong-Ki
    • Journal of the Korea Convergence Society
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    • v.10 no.4
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    • pp.33-38
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    • 2019
  • Recently, to support location-based services, there have been many researches which consider the spatial network. For this, there are many experimental data for data processing on the road network. However, the data to process the trajectory of moving objects are not suitable. Therefore, we propose index structure to process the trajectory data on the road network and the trajectory data generation algorithm. In addition, to prove efficiency of our index structure and algorithm, we show that edge-based trajectory data are generated through the proposed algorithm using the map data of San Francisco Bay.

Design an Indexing Structure System Based on Apache Hadoop in Wireless Sensor Network

  • Keo, Kongkea;Chung, Yeongjee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.45-48
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    • 2013
  • In this paper, we proposed an Indexing Structure System (ISS) based on Apache Hadoop in Wireless Sensor Network (WSN). Nowadays sensors data continuously keep growing that need to control. Data constantly update in order to provide the newest information to users. While data keep growing, data retrieving and storing are face some challenges. So by using the ISS, we can maximize processing quality and minimize data retrieving time. In order to design ISS, Indexing Types have to be defined depend on each sensor type. After identifying, each sensor goes through the Indexing Structure Processing (ISP) in order to be indexed. After ISP, indexed data are streaming and storing in Hadoop Distributed File System (HDFS) across a number of separate machines. Indexed data are split and run by MapReduce tasks. Data are sorted and grouped depend on sensor data object categories. Thus, while users send the requests, all the queries will be filter from sensor data object and managing the task by MapReduce processing framework.

Object Detection Using Combined Random Fern for RGB-D Image Format (RGB-D 영상 포맷을 위한 결합형 무작위 Fern을 이용한 객체 검출)

  • Lim, Seung-Ouk;Kim, Yu-Seon;Lee, Si-Woong
    • The Journal of the Korea Contents Association
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    • v.16 no.9
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    • pp.451-459
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    • 2016
  • While an object detection algorithm plays a key role in many computer vision applications, it requires extensive computation to show robustness under varying lightning and geometrical distortions. Recently, some approaches formulate the problem in a classification framework and show improved performances in object recognition. Among them, random fern algorithm drew a lot of attention because of its simple structure and high recognition rates. However, it reveals performance degradation under the illumination changes and noise addition, since it computes patch features based only on pixel intensities. In this paper, we propose a new structure of combined random fern which incorporates depth information into the conventional random fern reflecting 3D structure of the patch. In addition, a new structure of object tracker which exploits the combined random fern is also introduced. Experiments show that the proposed method provides superior performance of object detection under illumination change and noisy condition compared to the conventional methods.

Implementation of augmented reality using parallel structure (병렬구조를 이용한 증강현실 구현)

  • Park, Tae-Ryong;Heo, Hoon;Kwak, Jae-Chang
    • Journal of IKEEE
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    • v.17 no.3
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    • pp.371-377
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    • 2013
  • This thesis propose an efficient parallel structure method for implementing a FAST and BRIEF algorithm based Augmented Reality. SURF algorithm that is well known in the object recognition algorithms is robust in object recognition. However, there is a disadvantage for real time operation because, SURF implementation requires a lot of computation. Therefore, we used a FAST and BRIEF algorithm for object recognition, and we improved Conventional Parallel Structure based on OpenMP Library. As a result, it achieves a 70%~100% improvement in execution time on the embedded system.

A Study on the Design of Railway Electornic Interlocking Software Based on Real-Time Object-Oriented Modeling Technique (ROOM기법을 이용한 전자연동 소프트웨어 설계에 관한 연구)

  • Kim, Jong-Sun;Yoo, Ji-Yoon
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.9
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    • pp.439-446
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    • 2001
  • This paper considers the design technique of the real-time control algorithm to implement the electronic interlocking system which is the most important station control system in railway signal field. The proposed technique consists of the structure design and the detail design which are based on the ROOM(Real-Time Object-Oriented Modeling). The structure design is designed with a modeling using the heuristic search technique which, at first, catch and make out the specific requested condition, and then, is designed on the requested condition. The detail design can be implemented if it may get the satisfying values through the repetitive modeling after comparing and examining the data obtained from the structure design in order for the more reliable and accurate system to be implemented. The technique proposed in this paper is implemented with C++ language which is easy to be transferred and compatible with the existing interfaces, and also the operating system is designed and simulated on the VRTX which is a real-time operating system. This proposed technique is applied to the typical station model in order to prove the validity as verifying the performance of the modeled station.

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A Study on Development of SGML Repository System Based on DTD-dependent Schema (DTD 의존 스키마에 기반한 SGML 문서 저장 시스템 개발에 관한 연구)

  • Kim, Hyeon-Gi;No, Dae-Sik;Gang, Hyeon-Gyu
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.5
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    • pp.1153-1165
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    • 1999
  • In various fields of information technology, it is growing up the needs about dynamic content management systems to store and manage SGML(Standard Generalized Markup language) documents in a database system. In this paper, we consider the issue of storing SGML documents that having complex hierarchical structure into a database system, and then propose a data model based on ODMG(Object Database Management Group) object model in order to store SGML documents without loss of information. Because the proposed data model reflects physical element structure and logical entity structure of SGML documents, it is able to store the SGML document in a database system at the system at the element- level granularity without any information loss. And also the proposed data model can be adapted among ODMG-compliant object database management systems. Finally, we will discuss on the implementation details of SGML repository system supports the functionality of automatic database schema creation for any DTD(Document Type Definition0, the functionality of storing the SGML document, the functionality of dynamic document assembly from stored database objects to SGML document, and the functionality of indexing and searching for database objects.

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A SHdy on the Development of an Expert System for Chemical Plant Diagnosis Fault -An Object Description System based on Functional Structure- (화학 플랜트의 고장원 탐색 전문가 시스템에 관한 연구 -기능구조에 의한 대상의 지식표현 방법-)

  • 황규석
    • Journal of the Korean Society of Safety
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    • v.7 no.2
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    • pp.14-23
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    • 1992
  • A methodology for developing an object description system based on functional-structure of chemical plant is proposed. A knowledge base for chemical plant fault diagnosis is also organized in a generic fashion using the heuristic knowledge of human operators. A plant can be seen as a hierarchical set of subsystems. Each subsystem is called a SCOPE. The state of the plant and the behavior of each subsystem is managed by the SCOPES. A computer-based system based on thls methodology and knowledge base has been developed and applied to the subprocess of ethylene plant to evaluate the effectiveness of the methodology.

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Rend 3D R-tree: An Improved Index Structure in Moving Object Database Based on 3D R-tree (Rend 3D R-tree : 3D R-tree 기반의 이동 객체 데이터베이스 색인구조 연구)

  • Ren XiangChao;Kee-Wook Rim;Nam Ji Yeun;Lee KyungOh
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.878-881
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    • 2008
  • To index the object's trajectory is an important aspect in moving object database management. This paper implements an optimizing index structure named Rend 3D R-tree based on 3D R-Tree. This paper demonstrates the time period update method to reconstruct the MBR for the moving objects in order to decrease the dead space that is produced in the closed time dimension of the 3D R-tree, then a rend method is introduced for indexing both current data and history data. The result of experiments illustrates that given methods outperforms 3D R-Tree and LUR tree in query processes.