• 제목/요약/키워드: Application accuracy

검색결과 3,295건 처리시간 0.025초

Application of Multiple Threshold Values for Accuracy Improvement of an Automated Binary Change Detection Model

  • Yu, Byeong-Hyeok;Chi, Kwang-Hoon
    • 대한원격탐사학회지
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    • 제25권3호
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    • pp.271-285
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    • 2009
  • Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

토공현장 적용성 검증을 위한 MMS 정밀도 분석 (MMS Accuracy Analysis for Earthwork Site Application)

  • 박재우;김석
    • 한국산업융합학회 논문집
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    • 제22권2호
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    • pp.183-189
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    • 2019
  • Researches utilizing the fourth industrial revolution technology are being conducted as a breakthrough for improving the earthworker productivity. In order to make the earthwork site smarter, it is necessary to digitize the construction site topography at first. For this purpose, photogrammetry using drones and LiDAR on MMS have been recently used. The purpose of this study is to analyze the accuracy of LiDAR by installation angles for verifying the application of MMS in the construction site. As a result of comparing the coordinates measured by the total station and the LiDAR, a small error of about 1-2 centimeters was shown. It is confirmed that MMS could be well applied to the earthwork site. In addition, there was no significant difference in the accuracy of the acquired coordinates according to the installation angle of the LiDAR, but the shape of the point clouds was different. The larger the installation angle, the better the shape of the site terrain is measured.

BIM 적용을 위한 공간정보의 정확도 기반 활용성 평가 (Accuracy-based Evaluation of the Utilization of Spatial Information for BIM Application)

  • 김두표
    • 한국산업융합학회 논문집
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    • 제26권4_2호
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    • pp.669-678
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    • 2023
  • Recently, spatial information has been applied to various fields and its usability is increasing day by day. In particular, in the field of civil engineering and construction, BIM based on spatial information is being applied to all construction industries and related research has been conducted. BIM is a technology that utilizes spatial information from the design phase and aids in the construction and maintenance of buildings, including the management of their attributes. However, to apply BIM technology to existing buildings, it takes a lot of time and money to produce models based on design drawings along with current surveying. In this study, quantitative and qualitative analysis was conducted to determine the applicability of the acquired data and the applicability of BIM by generating data and analyzing the accuracy using UAV images and ground lidar, which are representative spatial information acquisition methods. Quantitative analysis revealed that TLS (Terrestrial Laser Scanner) showed reliable accuracy in both planar and elevation measurements, whereas unmanned aerial images exhibited lower accuracy in elevation measurements, resulting in reduced reliability. Qualitative analysis indicated that neither TLS nor unmanned aerial images alone provided perfect completeness. However, the combination of both spatial information sources, tailored to specific needs, resulted in the most comprehensive completeness. Therefore, it is concluded that the appropriate utilization of spatial information acquired through unmanned aerial images and TLS holds the potential for application in the fields of BIM and reverse engineering.

Indoor Environment Drone Detection through DBSCAN and Deep Learning

  • Ha Tran Thi;Hien Pham The;Yun-Seok Mun;Ic-Pyo Hong
    • 전기전자학회논문지
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    • 제27권4호
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    • pp.439-449
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    • 2023
  • In an era marked by the increasing use of drones and the growing demand for indoor surveillance, the development of a robust application for detecting and tracking both drones and humans within indoor spaces becomes imperative. This study presents an innovative application that uses FMCW radar to detect human and drone motions from the cloud point. At the outset, the DBSCAN (Density-based Spatial Clustering of Applications with Noise) algorithm is utilized to categorize cloud points into distinct groups, each representing the objects present in the tracking area. Notably, this algorithm demonstrates remarkable efficiency, particularly in clustering drone point clouds, achieving an impressive accuracy of up to 92.8%. Subsequently, the clusters are discerned and classified into either humans or drones by employing a deep learning model. A trio of models, including Deep Neural Network (DNN), Residual Network (ResNet), and Long Short-Term Memory (LSTM), are applied, and the outcomes reveal that the ResNet model achieves the highest accuracy. It attains an impressive 98.62% accuracy for identifying drone clusters and a noteworthy 96.75% accuracy for human clusters.

정적 및 동적 분석을 이용한 크로스 체크기반 취약점 분석 기법 (A Cross-check based Vulnerability Analysis Method using Static and Dynamic Analysis)

  • 송준호;김광직;고용선;박재표
    • 한국산학기술학회논문지
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    • 제19권12호
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    • pp.863-871
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    • 2018
  • 본 논문에서는 기존의 취약점 분석 도구들의 미탐지, 오탐지, 과탐지를 발생시켜 정확한 취약점 탐지를 어렵게 하는 문제점을 해결하고 분석 대상이 되는 어플리케이션의 위험도를 평가하여 안전한 어플리케이션을 개발하거나 관리할 수 있는 정적 및 동적 분석을 이용한 크로스 체크기반의 취약점 탐지 기법을 제안한다. 또한 각각의 취약점이 가지고 있는 자체 위험도를 계산하고 정확도를 높인 취약점 탐지 기법을 바탕으로 최종적인 어플리케이션의 위험도를 평가, 제시함으로서 안전한 어플리케이션의 개발 및 운영을 돕는다. 제안하는 기법은 정적 분석 및 동적 분석 기법을 사용하는 도구들의 상호작용을 통해 각 기법의 단점들을 극복하여 취약점 탐지 정확도를 향상시킨다. 또한 기존의 취약점 위험도평가 시스템은 취약점 자체 위험도에 대해서만 평가하였으나, 제안하는 위험도 평가는 취약점 자체 위험도와 탐지 정확도를 복합적으로 반영하여 어플리케이션이 얼마나 위험에 노출되어 있는지를 평가한다. 제안하는 기법은 CWE에서 SANS top 25의 상위 10위 항목을 기준으로 기존의 분석 도구들과 탐지 가능한 목록, 탐지 정확도를 비교분석하였으며, 기존의 취약점 위험도에 대한 정량적 평가 시스템과 제안하는 어플리케이션 위험도 평가 결과를 비교 분석 및 평가하였다. 제안하는 기법으로 프로토타입 분석 툴을 구현하여 실험을 통해 어플리케이션의 취약점을 분석하였을 때, 기존의 분석 도구들의 취약점 탐지 능력보다 우수한 것으로 나타났다.

정상운영기간동안의 KOMPSAT-3A호 주요 영상 품질 인자별 특성 (Characteristics of KOMPSAT-3A Key Image Quality Parameters During Normal Operation Phase)

  • 서두천;김현호;정재헌;이동한
    • 대한원격탐사학회지
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    • 제36권6_2호
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    • pp.1493-1507
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    • 2020
  • KOMPSAT-3A는 2015년 3월 발사하여 약 6개월의 기간 동안 초기 검보정을 수행한 이후 지난 8년 동안 성공적으로 KOMPSAT-3A 자료를 사용자들에게 배포하였으며, 수집된 영상 자료는 지도제작, GIS, 국토관리 등의 다양한 분야에서 정성적, 정량적 정보 추출의 기초 자료로 활용되고 있다. 한국항공우주연구원에서는 KOMPSAT-3A의 영상제품군에서 추출되는 정보의 정확도 및 신뢰도를 확보하기 위해 주기적으로 영상 품질과 인공위성 하드웨어 특성을 확인하고 있다. 또한 KOMPSAT-3A의 탑재체, 자세제어 센서들의 노후화에 따른 영상 품질 저하 현상을 최소화하기 위해 지속적인 영상 품질 개선 작업을 수행하고 있다. 본 논문에서는 KOMPSAT-3A 개발 단계에서 정의된 발사 전후의 검보정 주요 과정 및 대표 영상 품질 인자인 MTF, SNR, Location accuracy 측정 방법을 설명하였다. 이를 바탕으로 발사 후 초기 LEOP Cal/Val이 완료된 이후 측정된 영상 품질 인자별 성능값과 최근 2016년부터 2020년 5월까지 KOMPSAT-3A호의 주요 품질 인자인 MTF, SNR, Location accuracy 현황과 특성을 기술하였다.

Effects of pelvic stability on instep shooting speed and accuracy in junior soccer players

  • Sung, Ha-Rim;Shin, Won-Seob
    • Physical Therapy Rehabilitation Science
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    • 제7권2호
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    • pp.78-82
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    • 2018
  • Objective: The purpose of this study was to determine the effect of wearing a pelvic compression belt on ball speed and accuracy in instep shoots of youth soccer players. Design: Randomized cross-over design. Methods: We included 20 male junior soccer players with experience of more than 5 years. Participants were randomly assigned to two conditions: application of a pelvic compression belt and instep shooting or no application. Instep shooting was performed three times at a distance of 20 meters from the position of the goal post, and the ball speed was measured using a speed gun at a position 5 meters behind the goal post. The shooting accuracy was measured based on a 5-point scale. The shooting accuracy was measured by scoring 5 points at 2.44 meters in the middle of the goal area of area A, 3 points at 2.44 meters in the goal area of area B, and 0 in the case of shooting outside the goal area C. Results: After applying a pelvic compression belt, the mean speed of the ball was significantly increased (p<0.05). The maximum speed of the ball was significantly increased (p<0.05). The accuracy of the ball was significantly increased (p<0.05). Conclusions: Through this study, we expect that the use of the pelvic compression belt can be applied as a training method to improve the shooting ability of soccer players. Clinically, pelvic compression belts are expected to help rehabilitation soccer players to improve their shooting accuracy.

Deep Learning Frameworks for Cervical Mobilization Based on Website Images

  • Choi, Wansuk;Heo, Seoyoon
    • 국제물리치료학회지
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    • 제12권1호
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    • pp.2261-2266
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    • 2021
  • Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

Mapping of Post-Wildfire Burned Area Using KOMPSAT-3A and Sentinel-2 Imagery: The Case of Sokcho Wildfire, Korea

  • Nur, Arip Syaripudin;Park, Sungjae;Lee, Kwang-Jae;Moon, Jiyoon;Lee, Chang-Wook
    • 대한원격탐사학회지
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    • 제36권6_2호
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    • pp.1551-1565
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    • 2020
  • On April 4, 2019, a forest fire started in Goseong County and lasted for three days, burning the neighboring areas of Sokcho. The strong winds moved the blaze from one region to another region and declared the worst wildfire in South Korea in years. More than 1,880 facilities, including 400 homes, were burnt down. The fire burned a total area of 529 hectares (1,307 acres), which involved 13,000 rescuers and 16,500 military troops to control the fire occurrence. Thousands of people were evacuated, and two people are dead. This study generated post-wildfire maps to provide necessary data for evacuation and mitigation planning to respond to this destructive wildfire, also prevent further damage and restore the area affected by the wildfire. This study used KOMPSAT-3A and Sentinel-2 imagery to map the post-wildfire condition. The SVM showed higher accuracy (overall accuracy 95.29%) compared with ANN (overall accuracy of 94.61%) for the KOMPSAT-3A. Moreover, for Sentinel-2, the SVM attained a higher accuracy (overall accuracy of 91.52%) than the ANN algorithm (overall accuracy 90.11%). In total, four post-wildfire burned area maps were generated; these results can be used to assess the area affected by the Sokcho wildfire and wildfire mitigation planning in the future.

CAD에 의한 치수정밀 보정값 적용에 관한 연구 (A study on application of dimension accuracy compensation by CAD)

  • 이시헌;원시태
    • Design & Manufacturing
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    • 제2권1호
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    • pp.11-14
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    • 2008
  • we can save a development cost and time as computer was used in tool and die design of car fields in die manufacture process. Dimension accuracy errors such as springback, springgo, overcrown and twist were reduced product accuracy and caused trouble to assembly each parts of car. In this paper, CADCEUS was used to modify and optimize results of deflection for a tail gate panel of car parts in order to reduce dimension accuracy errors by springback in sheet metal forming. As CADCEUS was used to apply for a tail gate panel, the time for quality to improve was reduced to 30%.

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