• Title/Summary/Keyword: Small target detection

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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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    • v.16 no.7
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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.

Distance Measurement of Small Moving Object using Infrared Stereo Camera (적외선 스테레오 카메라를 이용한 소형 이동체의 거리 측정)

  • Oh, Jun-Ho;Lee, Sang-Hwa;Lee, Boo-Hwan;Park, Jong-Il
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.3
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    • pp.53-61
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    • 2012
  • This paper proposes a real-time distance measurement system of high temperature and high speed target using infrared stereo camera. We construct an infrared stereo camera system that measure the difference between target and background temperatures for automatic target measurement. First, the proposed method detects target region based on target motion and intensity variation of local region using difference between target and background temperatures. Second, stereo matching by left and right target information is used to estimate disparity about real-time distance of target. In the proposed method using infrared stereo camera system, we compare distances in three dimension trajectory measuring instrument and in infrared stereo camera measurement. In this experiment from three video data, the result shows an average 9.68% distance error rate. The proposed method is suitable for distance and position measurement of varied targets using infrared stereo system.

Microgravity for Engineering and Environmental Applications (토목.환경 응용을 위한 고정밀 중력탐사)

  • Park, Yeong-Sue;Rim, Hyoung-Rae;Lim, Mu-Taek
    • 한국지구물리탐사학회:학술대회논문집
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    • 2007.12a
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    • pp.15-25
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    • 2007
  • Gravity method could be one of the most effective tool for evaluating the soundness of basement which is directly correlated with density and its variations. Moreover, Gravimeter is easy to handle and strong to electromagnetic noises. But, gravity anomaly due to the target structures in engineering and environmemtal applications are too small to detect, comparing to the external changes, such as, elevation, topography, and regional geological variations. Gravity method targeting these kinds of small anomaly sources with high precision usually called microgravity. Microgravimetry with precision and accuracy of few ${\mu}Gal$, can be achieved by the recent high-resolution gravimeter, careful field acquisition, and sophisticated processing, analysis, and interpretation routines. This paper describes the application of the microgravity, such as, density structure of a rock fill dam, detection of abandoned mine-shaft, detection and mapping of karstic cavities in limestone terrains, and time-lapse gravity for grout monitoring. The case studies show how the gravity anomalies detect the location of the targets and reveal the geologic structure by mapping density distributions and their variations.

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Dividing Occluded Pedestrians in Wide Angle Images for the Vision-Based Surveillance and Monitoring (시각 기반 감시 및 관측을 위한 광각 영상에서의 중첩된 보행자 구분)

  • Park, Jaehyeong;Do, Yongtae
    • Journal of Sensor Science and Technology
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    • v.24 no.1
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    • pp.54-61
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    • 2015
  • In recent years, there has been increasing use of automatic surveillance and monitoring systems based on vision sensors. Humans are often the most important target in the systems, but processing human images is difficult due to the small sizes and flexible motions. Particularly, occlusion among pedestrians in camera images brings practical problems. In this paper, we propose a novel method to separate image regions of occluded pedestrians. A camera equipped with a wide angle lens is attached to the ceiling of a building corridor for sensing pedestrians with a wide field of view. The output images of the camera are processed for the human detection, tracking, identification, distortion correction, and occlusion handling. We resolve the occlusion problem adaptively depending on the angles and positions of their heads. Experimental results showed that the proposed method is more efficient and accurate compared with existing methods.

Recent Advances in Nanozyme Research for Disease Diagnostics (질병진단을 위한 나노자임 연구의 최근 동향)

  • Shin, Ho Yun;Yoon, Tae Young;Kim, Moon Il
    • KSBB Journal
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    • v.30 no.1
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    • pp.1-10
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    • 2015
  • Nanomaterial-based artificial enzymes (Nanozymes) have attracted recent attention because of their unique advantageous characteristics such as excellent robustness and stability, low-cost production by facile scale-up, and longterm preservation capability that are critically required as an alternative to natural enzymes. These nanozymes exhibit natural enzyme-like activity, and they have been applied to diverse kinds of detection methods for disease-associated biomolecules such as DNAs, proteins, cells, and small molecules including glucose. To highlight the progress in the field of disease diagnostics using nanozyme, this review discusses many nanozyme-based detection methods categorized by the types of target biomolecules. Finally, we address the current challenges and perspectives for the widespread utilization of nanozyme-based disease diagnostics.

Analysis on Figure of Merits of Small SAR Constellation Satellites for Targets Detection (표적탐지를 위한 소형 SAR 군집위성의 성능지수 분석)

  • Song, Sua;Kim, Hongrae;Chang, Young-Keun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.47 no.2
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    • pp.130-142
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    • 2019
  • For a preemptive strike against a Time Critical Target(TCT), such as Transporter-Erector-Launcher(TEL), the detection capability of capturing launch signals in the Area of Interest(AoI) is important. In this study, the characteristics of the revisit time and the response time of 6~48 small SAR constellation satellites were analyzed. In particular, the revisit time was analyzed for all regions of North Korea and specific regions, and the response time was classified into [Scenario 1] to identify fixed targets and [Scenario 2] to detect and identify moving targets. In particular, the response time analysis for the TCT detection mission operation in [scenario 2] was performed through optimization analysis of observation cumulative coverage for a specific area. Finally, the configuration of constellation satellites for optimal performance of the detection mission was estimated.

Identification of Caenorhabditis elegans MicroRNA Targets Using a Kernel Method

  • Lee, Wha-Jin;Nam, Jin-Wu;Kim, Sung-Kyu;Zhang, Byoung-Tak
    • Genomics & Informatics
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    • v.3 no.1
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    • pp.15-23
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    • 2005
  • Background MicroRNAs (miRNAs) are a class of noncoding RNAs found in various organisms such as plants and mammals. However, most of the mRNAs regulated by miRNAs are unknown. Furthermore, miRNA targets in genomes cannot be identified by standard sequence comparison since their complementarity to the target sequence is imperfect in general. In this paper, we propose a kernel-based method for the efficient prediction of miRNA targets. To help in distinguishing the false positives from potentially valid targets, we elucidate the features common in experimentally confirmed targets. Results The performance of our prediction method was evaluated by five-fold cross-validation. Our method showed 0.64 and 0.98 in sensitivity and in specificity, respectively. Also, the proposed method reduced the number of false positives by half compared with TargetScan. We investigated the effect of feature sets on the classification of miRNA targets. Finally, we predicted miRNA targets for several miRNAs in the Caenorhabditis elegans (C. elegans) 3' untranslated region (3' UTR) database. Condusions The targets predicted by the suggested method will help in validating more miRNA targets and ultimately in revealing the role of small RNAs in the regulation of genomes. Our algorithm for miRNA target site detection will be able to be improved by additional experimental­knowledge. Also, the increase of the number of confirmed targets is expected to reveal general structural features that can be used to improve their detection.

Radar Target Segmentation via Histogram Chord Search Method (히스토그램 현 탐색방식에 의한 레이다 표적 분할 알고리즘)

  • Choi, Beyung-Gwan;Kim, WhAn-Woo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.195-202
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    • 2005
  • An adaptive segmentation algorithm is used to efficiently target decisions in local non-stationary images. Until now, several adaptive approaches have been proposed as a method of segmentation. However, they can't be directly used for radar target detection because a radar signal has different characteristics from general images. Generally, a histogram of radar signal shows that targets have a relatively small number of frequency functions compared to the background and distribution of background, which have several shapes as the environment changes. In this paper, we propose an adaptive segmentation algorithm using a histogram chord which is a right-down line from maximum pick of frequency function. The proposed method provides thresholds which are optimum for several radar environments because the used chord for threshold search is not significantly effected by interference conditions. Simulation results show that the proposed method is superior to the traditional algorithms, global threshold method and distribution median method, with respect to detection performance.

The Principle and Trends of CRISPR/Cas Diagnosis (CRISPR/Cas 진단의 원리와 현황)

  • Park, Jeewoong;Kang, Bong Keun;Shin, Hwa Hui;Shin, Jun Geun
    • Journal of Biomedical Engineering Research
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    • v.42 no.3
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    • pp.125-142
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    • 2021
  • The POCT (point-of-care test) sensing that has been a fast-developing field is expected to be a next generation technology in health care. The POCT sensors for the detection of proteins, small molecules and especially nucleic acids have lately attracted considerable attention. According to the World Health Organization (WHO), the POCT methods are required to follow the ASSURED guidelines (Affordable, Sensitive, Specific, User- friendly, Robust and rapid, Equipment-free, Deliverable to all people who need the test). Recently, several CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) based diagnostic techniques using the sensitive gene recognition function of CRISPR have been reported. CRISPR/Cas (Cas, CRISPR associated protein) systems based detection technology is the most innovative gene analysis technology that is following the ASSURED guidelines. It is being re-emerged as a powerful diagnostic tool that can detect nucleic acids due to its characteristics that enable rapid, sensitive and specific analyses of nucleic acid. The first CRISPR-based diagnosis begins with the discovery of the additional function of Cas13a. The enzymatic cleavage occurs when the conjugate of Cas protein and CRISPR RNA (crRNA) detect a specific complementary sequence of the target sequence. Enzymatic cleavage occurs on not only the target sequence, but also all surrounding non-target single-stranded RNAs. This discovery was immediately utilized as a biosensor, and numerous sensor studies using CRISPR have been reported since then. In this review, the concept of CRISPR, the characteristics of the Cas protein required for CRISPR diagnosis, the current research trends of CRISPR diagnostic technology, and some aspects to be improved in the future are covered.

Drone Detection with Chirp-Pulse Radar Based on Target Fluctuation Models

  • Kim, Byung-Kwan;Park, Junhyeong;Park, Seong-Jin;Kim, Tae-Wan;Jung, Dae-Hwan;Kim, Do-Hoon;Kim, Taihyung;Park, Seong-Ook
    • ETRI Journal
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    • v.40 no.2
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    • pp.188-196
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    • 2018
  • This paper presents a pulse radar system to detect drones based on a target fluctuation model, specifically the Swerling target model. Because drones are small atypical objects and are mainly composed of non-conducting materials, their radar cross-section value is low and fluctuating. Therefore, determining the target fluctuation model and applying a proper integration method are important. The proposed system is herein experimentally verified and the results are discussed. A prototype design of the pulse radar system is based on radar equations. It adopts three different pulse modes and a coherent pulse integration to ensure a high signal-to-noise ratio. Outdoor measurements are performed with a prototype radar system to detect Doppler frequencies from both the drone frame and blades. The results indicate that the drone frame and blades are detected within an instrumental maximum range. Additionally, the results show that the drone's frame and blades are close to the Swerling 3 and 4 target models, respectively. By the analysis of the Swerling target models, proper integration methods for detecting drones are verified and can thus contribute to increasing in detectability.