• Title/Summary/Keyword: Multi-target detection

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The Influence of Stimulus Contrast and Color on Target Detection under Multiple Rapid Serial Visual Presentation (다중신속순차제시아래 자극의 명암대비 및 색상이 표적 탐지에 미치는 영향)

  • Park, Jong-Min;Kim, Giyeon;Hyun, Joo-Seok
    • Science of Emotion and Sensibility
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    • v.20 no.2
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    • pp.137-148
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    • 2017
  • The present study examined the effect of stimulus contrast and color on detection of a target embedded in streams of letters. In Experiment 1, each trial displayed four rapid serial visual presentation (RSVP) streams of letters (i.e., multi-RSVP), and each stream occupied one of four different locations. Each frame in the RSVP stream had four white distractors at the locations except one frame where a dim grey target was displayed at a location with three white distractors at the remaining locations. In the low-visibility target condition, the target's grey color was slightly darker than the background grey whereas much dimmer in the high-visibility condition. Participants were asked to report presence of a predesignated target as quickly and accurately as possible upon its detection in each trial, and their target detection turned out more accurate and quicker in the high-visibility than the low-visibility condition. In Experiment 2, the same RSVP displays and task as Experiment were used, but the grey target letters in the high-visibility condition were replaced with those of distinct chromatic colors. Participants detected target presence more accurately in the high-visibility condition, but the reaction time did not differ between the visibility conditions. The results indicate that higher stimulus contrast as well as distinct color can improve perception of a target stimulus displayed among visually-demanding background, but also suggest that stimulus contrast may play a more substantial role for such perceptual improvement.

A Study on the Optimal Data Association in Multi-Target Tracking by Hopfield Neural Network (홉필드 신경망을 이용한 다중 표적 추적이 데이터 결합 최적화에 대한 연구)

  • Lee, Yang-Weon;Jeong, Hong
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.6
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    • pp.186-197
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    • 1996
  • A multiple target tracking (MTT) problem is to track a number of targets in clusttered environment, where measurements may contain uncertainties of measurement origin due to clutter, missed detection, or other targets, as well as measurement noise errors. Hence, an MTT filter should be introduced to resolve this problem. In this paper, a neural network is rpoposed as an MTT filter.

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Single Ping Clutter Reduction Algorithm Using Statistical Features of Peak Signal to Improve Detection in Active Sonar System (능동소나 탐지 성능 향상을 위한 피크 신호의 통계적 특징 기반 단일 핑 클러터 제거 기법)

  • Seo, Iksu;Kim, Seongweon
    • The Journal of the Acoustical Society of Korea
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    • v.34 no.1
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    • pp.75-81
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    • 2015
  • In active sonar system, clutters degrade performance of target detection/tracking and overwhelm sonar operators in ASW (Antisubmarine Warfare). Conventional clutter reduction algorithms using consistency of local peaks are studied in multi-ping data and tracking filter research for active sonar was conducted. However these algorithms cannot classify target and clutters in single ping data. This paper suggests a single ping clutter reduction approach to reduce clutters in mid-frequency active sonar system using echo shape features. The algorithm performance test is conducted using real sea-trial data in heavy clutter density environment. It is confirmed that the number of clutters was reduced by about 80 % over the conventional algorithm while retaining the detection of target.

Modern Methods of Text Analysis as an Effective Way to Combat Plagiarism

  • Myronenko, Serhii;Myronenko, Yelyzaveta
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.242-248
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    • 2022
  • The article presents the analysis of modern methods of automatic comparison of original and unoriginal text to detect textual plagiarism. The study covers two types of plagiarism - literal, when plagiarists directly make exact copying of the text without changing anything, and intelligent, using more sophisticated techniques, which are harder to detect due to the text manipulation, like words and signs replacement. Standard techniques related to extrinsic detection are string-based, vector space and semantic-based. The first, most common and most successful target models for detecting literal plagiarism - N-gram and Vector Space are analyzed, and their advantages and disadvantages are evaluated. The most effective target models that allow detecting intelligent plagiarism, particularly identifying paraphrases by measuring the semantic similarity of short components of the text, are investigated. Models using neural network architecture and based on natural language sentence matching approaches such as Densely Interactive Inference Network (DIIN), Bilateral Multi-Perspective Matching (BiMPM) and Bidirectional Encoder Representations from Transformers (BERT) and its family of models are considered. The progress in improving plagiarism detection systems, techniques and related models is summarized. Relevant and urgent problems that remain unresolved in detecting intelligent plagiarism - effective recognition of unoriginal ideas and qualitatively paraphrased text - are outlined.

Optimal Sensor Placement in Multistatic Sonar (다중 상태 소나의 최적 수신망 배치)

  • Lee, Kwang-Hee;Han, Dong-Seog
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.5
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    • pp.630-634
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    • 2012
  • It is very important to place receiver in multistatic sonar. Inefficient placement of the receiver reduce detection probability and to increase the probability of detection should be used more receivers. Therefore, detection of targets in searching area, detection performance of limited receiver depends on how to place. Through the optimized receiver placement, detection area between each sonar as much as possible avoid duplication, as optimization, the minimum receiver can be maintained detection performance. In this paper we prove mathematical verification of maximum signal excess value based on sonar placement and we calculate a signal excess value by using computer simulations and suggest optimal sonar placement.

AdaBoost-based Real-Time Face Detection & Tracking System (AdaBoost 기반의 실시간 고속 얼굴검출 및 추적시스템의 개발)

  • Kim, Jeong-Hyun;Kim, Jin-Young;Hong, Young-Jin;Kwon, Jang-Woo;Kang, Dong-Joong;Lho, Tae-Jung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.11
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    • pp.1074-1081
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    • 2007
  • This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

Manhole Cover Detection from Natural Scene Based on Imaging Environment Perception

  • Liu, Haoting;Yan, Beibei;Wang, Wei;Li, Xin;Guo, Zhenhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.5095-5111
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    • 2019
  • A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

A Validation of Effectiveness for Intrusion Detection Events Using TF-IDF (TF-IDF를 이용한 침입탐지이벤트 유효성 검증 기법)

  • Kim, Hyoseok;Kim, Yong-Min
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1489-1497
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    • 2018
  • Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

A Disposable Grating-Integrated Multi-channel SPR Sensor Chip for Detection of Biomolecule (회절격자가 집적된 일회용 다중채널 SPR 생체분자 검출 칩)

  • Jin, Young-Hyun;Cho, Young-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.1
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    • pp.147-154
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    • 2009
  • This paper presents a grating~integrated SPR (Surface Plasmon Resonance) sensor chip for simple and inexpensive biomolecule detection. The grating-integrated SPR sensor chip has two sensing channels having a nano grating for SPR coupling. An external mirror is used for multi channel SPR sensing. The present sensor chip replaces bulky and expensive optical components, such as fiber-optic switches or special shaped prisms, resulting in a simple and inexpensive wavelength modulated multi-channel SPR sensing system. We fabricate a SPR sensor chip integrated with 835 nm-pitch gratings by a micromolding technique to reduce the fabrication cost. In the experimental characterization, the refractive index sensitivity of each sensing channel is measured as $321.8{\pm}8.1nm$/RI and $514.3{\pm}8.lnm$/RI, respectively. 0.5uM of the target biomolecule (streptavidin) was detected by a $1.13{\pm}0.16nm$ shift of the SPR dip in the 10%-biotinylated sample channel, while the SPR dip in the reference channel for environmental perturbation monitoring remained at the same position. From the experimental results, multi-channel biomolecule detection capability of the present grating-integrated SPR sensor chip has been verified. On the basis of the preliminary experiments, we successfully measured the binding reaction rate for the $2\;nM{\sim}200\;nM$ monoclonal-antibiotin, thus verifying biomolecule concentration detectability of the present SPR sensor chip. The binding reaction rates measured from the present SPR sensor chip agredd well with those from a commercialized SPR sensor.

Track Initiation and Target Tracking Filter Using LiDAR for Ship Tracking in Marine Environment (해양환경에서 선박 추적을 위한 라이다를 이용한 궤적 초기화 및 표적 추적 필터)

  • Fang, Tae Hyun;Han, Jungwook;Son, Nam-Sun;Kim, Sun Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.2
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    • pp.133-138
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    • 2016
  • This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.