• 제목/요약/키워드: Multi-Target

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목표중량 근사치 자동 설정을 위한 멀티헤드 조합시스템에 관한 연구 (A Study on Automated Multi-Channel Combination System for the Closest Target Weight)

  • 안용우;반갑수
    • 한국기계가공학회지
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    • 제14권6호
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    • pp.77-83
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    • 2015
  • This paper is a study of the functions required for the system to quantify the closest target weight by combining several random weights such as chips, snacks, fruits, and vegetables. The multi-head weigher is designed for high-performance applications requiring increased production rates and tight accuracy tolerances. This combination system has 12 heads considered in the form of a rectangular array of $2{\times}6$ or $3{\times}4$. Channel combination can usually occur between 1 and n, and the frequency was the highest with two or three combinations. Experimental result of a combination system for a total target weight was measured at the range from 100g to 500g by increments of 50g, and the average success rate was about 70%. The average elapsed time was about 1.7 seconds, which means it can be used for the packaging of agricultural products with a variety of items.

목적물 인식 및 자동 선택이 가능한 모바일 폰 용 자동초점 알고리즘 (Enhanced Auto-focus algorithm detecting target object with multi-window and fuzzy reasoning for the mobile phone)

  • 이상용;오승훈;김수원
    • 대한전자공학회논문지SD
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    • 제44권3호
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    • pp.12-19
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    • 2007
  • 본 논문에서는 피사체 인식 및 자동 선택이 가능한 모바일 폰 용 자동초점 알고리즘을 제안하였다. 제안된 알고리즘은 피사체 인식 단계와 목적물 자동 선택 단계로 구성된다. 피사체 인식 단계에서는 화면 전체에 배치된 다중 소형 측거점과 초점값 연산자를 사용하여 복수개의 피사체를 모바일 폰에 내장된 이미지 센서만을 사용하여 인식함으로써 기존의 적외선이나 초음파와 같은 외부 장치를 사용하는 방식과 달리 모바일 폰에서의 피사체 인식을 가능케 하고자 하였다 목적물 자동 선택 단계에서는 퍼지 멤버십 변수와 퍼지 추론을 통해 사용자가 촬영하고자 하는 목적물을 자동 선택하는데 이는 사진 기술이 없는 사용자라도 선명한 화질의 디지털 이미지를 획득할 수 있도록 하기 위함이다. 제안된 알고리즘은 프로그램 언어로 구현되었으며, 초점 거리 제어가 가능한 CCD 카메라와 PC를 사용하여 실시간으로 이미지를 분석, 검증하였다.

Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine

  • Lee, Soojin
    • 대한약침학회지
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    • 제18권3호
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    • pp.11-18
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    • 2015
  • Objectives: Systems biology is a novel subject in the field of life science that aims at a systems' level understanding of biological systems. Because of the significant progress in high-throughput technologies and molecular biology, systems biology occupies an important place in research during the post-genome era. Methods: The characteristics of systems biology and its applicability to traditional medicine research have been discussed from three points of view: data and databases, network analysis and inference, and modeling and systems prediction. Results: The existing databases are mostly associated with medicinal herbs and their activities, but new databases reflecting clinical situations and platforms to extract, visualize and analyze data easily need to be constructed. Network pharmacology is a key element of systems biology, so addressing the multi-component, multi-target aspect of pharmacology is important. Studies of network pharmacology highlight the drug target network and network target. Mathematical modeling and simulation are just in their infancy, but mathematical modeling of dynamic biological processes is a central aspect of systems biology. Computational simulations allow structured systems and their functional properties to be understood and the effects of herbal medicines in clinical situations to be predicted. Conclusion: Systems biology based on a holistic approach is a pivotal research methodology for understanding the mechanisms of traditional medicine. If systems biology is to be incorporated into traditional medicine, computational technologies and holistic insights need to be integrated.

Multi-resolution Fusion Network for Human Pose Estimation in Low-resolution Images

  • Kim, Boeun;Choo, YeonSeung;Jeong, Hea In;Kim, Chung-Il;Shin, Saim;Kim, Jungho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권7호
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    • pp.2328-2344
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    • 2022
  • 2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

Multi-level Cross-attention Siamese Network For Visual Object Tracking

  • Zhang, Jianwei;Wang, Jingchao;Zhang, Huanlong;Miao, Mengen;Cai, Zengyu;Chen, Fuguo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권12호
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    • pp.3976-3990
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    • 2022
  • Currently, cross-attention is widely used in Siamese trackers to replace traditional correlation operations for feature fusion between template and search region. The former can establish a similar relationship between the target and the search region better than the latter for robust visual object tracking. But existing trackers using cross-attention only focus on rich semantic information of high-level features, while ignoring the appearance information contained in low-level features, which makes trackers vulnerable to interference from similar objects. In this paper, we propose a Multi-level Cross-attention Siamese network(MCSiam) to aggregate the semantic information and appearance information at the same time. Specifically, a multi-level cross-attention module is designed to fuse the multi-layer features extracted from the backbone, which integrate different levels of the template and search region features, so that the rich appearance information and semantic information can be used to carry out the tracking task simultaneously. In addition, before cross-attention, a target-aware module is introduced to enhance the target feature and alleviate interference, which makes the multi-level cross-attention module more efficient to fuse the information of the target and the search region. We test the MCSiam on four tracking benchmarks and the result show that the proposed tracker achieves comparable performance to the state-of-the-art trackers.

다중표적 추적을 위한 광 JTC의 효과적인 이진화 방법 (The Effective Binarization Method of Optical JTC for Multitarget Tracking)

  • 이상이;서춘원;김은수
    • 전자공학회논문지A
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    • 제31A권5호
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    • pp.76-84
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    • 1994
  • Recently, Optical BJTC as a new approach for real-time multi-target tracking has been intensively studied. But the conventional system has some problems in the practical applications such as the false alarm and target missing and low correlation efficiency, and these poor performances are analyzed to be deeply dependent on the binarization method. So, in this paper, a new BJTC system which has the improved performances in target discrimination and diffraction efficiency is suggested, which is based on the JTPS having the same properties with those of the matched filter and new power spectrum binarization method to use effectively the high frequency components of the JTPS signal. Through the computer simulation and some experiments, the performances of the new BJTC tracking system are analyzed and proved to be superior to those of the conventional system baseds on Median method in multi- target tracking problems.

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An Object-Level Feature Representation Model for the Multi-target Retrieval of Remote Sensing Images

  • Zeng, Zhi;Du, Zhenhong;Liu, Renyi
    • Journal of Computing Science and Engineering
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    • 제8권2호
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    • pp.65-77
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    • 2014
  • To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

Development of Acoustic Target Strength Analysis System for Submarine

  • Kwon, Hyun-Wung;Hong, Suk-Yoon;Jeon, Jae-Jin;Song, Jee-Hun
    • International Journal of Ocean System Engineering
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    • 제3권3호
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    • pp.158-163
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    • 2013
  • The acoustic target strength (TS) is one of the most important parameters for a submarine's stealth design. Because modem submarines are larger than their predecessors, TS must be managed at each design stage in order to reduce it. To predict the TS of a submarine, TASTRAN R1 was developed based on a Kirchhoff approximation in a high-frequency range. This program can present TS values that include multi-bounce effect in the exterior and interior of the structure by combining geometric optics (GO) and physical optics (PO) methods, anechoic coating effect by using the reflection coefficient, and response time pattern for a detected target. In this paper, TS calculations for a submarine model with the above effects are simulated by using this developed program, and the TS results are discussed.

다중 대역 다중 모드 SDR 레이다 플랫폼 개발 (Development of Multi-Band Multi-Mode SDR Radar Platform)

  • 곽영길;우인상
    • 한국전자파학회논문지
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    • 제27권11호
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    • pp.949-958
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    • 2016
  • 본 논문은 다중대역 및 다중모드의 레이다 기능을 갖는 새로운 SDR(Software Defined Radar) 플랫폼의 개발 결과를 제시한다. SDR 하드웨어 플랫폼은 다중대역의 S, X, 그리고 K 밴드의 교체 가능한 RF 송수신기 및 안테나 모듈과 프로그램 가능한 신호처리기 모듈로 구현된다. 소프트웨어 플랫폼은 다중모드의 CW, Pulse, FMCW, LFM Chirp 파형 발생과 적응 가능한 신호처리 알고리즘 라이브러리 모듈 및 개방형 API 소프트웨어 모듈로 구현된다. SDR 플랫폼의 레이다 통합시험을 통하여 동작 성능을 실시간으로 검증하였으며, 또한 현장 활용시험을 통하여 지상 표적 및 비행체 드론 표적을 성공적으로 탐지하여 시험 결과를 제시하였다.

Failure and Phase Transformation Mechanism of Multi-Layered Nitride Coating for Liquid Metal Injection Casting Mold

  • Jeon, Changwoo;Lee, Juho;Park, Eun Soo
    • 한국재료학회지
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    • 제31권6호
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    • pp.331-338
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    • 2021
  • Ti-Al-Si target and Cr-Si target are sputtered alternately to develop a multi-layered nitride coating on a steel mold to improve die-casting lifetime. Prior to the multi-layer deposition, a CrN layer is developed as a buffer layer on the mold to suppress the diffusion of reactive elements and enhance the cohesive strength of the multi-layer deposition. Approximately 50 nm CrSiN and TiAlSiN layers are deposited layer by layer, and form about three ㎛-thickness of multi-layered coating. From the observation of the uncoated and coated steel molds after the acceleration experiment of liquid metal injection casting, the uncoated mold is severely eroded by the adhesion of molten metallic glass. On the other hand, the multi-layer coating on the mold prevents element diffusion from the metallic glass and mold erosion during the experiment. The multi-layer structure of the coating transforms the nano-composite structured coating during the acceleration test. Since the nano-composite structure disrupts element diffusion to molten metallic glass, despite microstructure changes, the coating is not eroded by the 1,050 ℃ molten metallic glass.