• Computers and Concrete
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• v.17 no.6
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• pp.831-848
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• 2016

This study aims to characterize the multiple cracking behavior of HTPP-ECC (High tenacity polypropylene fiber reinforced engineered cementitious composites) by Digital Image Correlation (DIC) Method. Digital images have been captured from a dogbone shaped HTPP-ECC specimen exhibiting 3.1% tensile ductility under loading. Images analyzed by VIC-2D software and ${\varepsilon}_{xx}$ strain maps have been obtained. Crack widths were computed from the ${\varepsilon}_{xx}$ strain maps and crack width distributions were determined throughout the specimen. The strain values from real LVDTs were also compared with virtual LVDTs digitally attached on digital images. Results confirmed that it is possible to accurately monitor the initiation and propagation of any single crack or multiple cracks by DIC at the whole interval of testing. Although the analysis require some post-processing operations, DIC based crack analysis methodology can be used as a promising and versatile tool for quality control of HTPP-ECC and other strain hardening composites.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.267-277
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• 2020

It is important to understand the exact habitat distribution of endangered species because of their decreasing numbers. In this study, we build a system with a deep learning module that collects the image data of endangered animals, processes the data, and saves the data automatically. The system provides a more efficient way than human effort for classifying images and addresses two problems faced in previous studies. First, specious answers were suggested in those studies because the probability distributions of answer candidates were calculated even if the actual answer did not exist within the group. Second, when there were more than two entities in an image, only a single entity was focused on. We applied an object detection algorithm (YOLO) to resolve these problems. Our system has an average precision of 86.79%, a mean recall rate of 93.23%, and a processing speed of 13 frames per second.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.103-104
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• 2022

Cracks may occur in reinforced concrete (RC) structures due to various physical and chemical factors, and the growth of cracks causes deterioration of the structure's performance. It is important to prevent the expansion of cracks through periodic diagnosis of cracks in structures. In order to enable free crack exploration even in a narrow space, a construction robot using a Mecanum wheel that can move up, down, left and right and rotate in place was designed. High-quality crack images were periodically collected through the camera, and the image fragments stored during the exploration were combined into a single photo after the exploration was completed. The robot detected cracks with a width of 0.2 mm or more on the concrete probe surface with an accuracy of about 90% or more.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.26 no.2
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• pp.119-129
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• 2024

Knowledge of the venous anatomy is essential for appropriately treating dural arteriovenous fistulas (AVFs). It is challenging to determine the overall venous structure despite performing selective angiography for dural AVFs with feeder from multiple selected arteries. This is because only a part of the veins can be observed through the shunt in the selected artery. Therefore, after performing selective angiography of all vessels to understand the approximate venous anatomy, the venous anatomy can be easily understood by closely examining the source image of computed tomographic angiography or magnetic resonance angiography. Through this, it is possible to specify the vein that is to be blocked (target embolization), thereby avoiding extensive blocking of the vein and avoiding various complications. In the case of dural AVF with feeder from single selected artery, if the multiplanar reconstruction image of the three-dimensional rotational computed tomography obtained by performing angiography is analyzed thoroughly, a shunted pouch can be identified. If embolization is performed by targeting this area, unnecessary sinus total packing can be avoided.

• Proceedings of the Optical Society of Korea Conference
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• 2009.10a
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• pp.165-166
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• 2009

A hologram was recorded with two-dimensional scanning of an optical fiber connected to a single-photon counting detector under ultra-weak illumination. The object image was clearly reconstructed in a computer from the hologram. The dependence of hologram quality on the illumination light intensity was estimated.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.429-432
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• 2001

본 논문에서는 Cascode FETs 구조를 능동필터로 동작시켜 이미지제거 특성을 분석하였으며, Cascode형 자기발진 믹서를 설계하였다. Ku-band 대역에서 모의실험 결과 Cas code FETs형 자기발진믹서에서 이미지성분이 -254Bc 개선되었으며, Single FET형 자기발진믹서와 비교해서 -23dBc 이상 개선됨을 확인할 수 있었다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.237-240
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• 2001

본 논문은 단일 뷰-포인트 카메라 모델을 이용하여 무-특징 환경 (non-feature environment)에서의 영상 모자이킹 알고리즘을 제안한다. 특징 환경에서 영상의 기하구조를 만들어 내고 이 기하구조를 무-특징 환경에 적용시켜 모자이크 영상을 얻는다.

• ETRI Journal
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• v.38 no.4
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• pp.767-775
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• 2016

Automatic container code recognition from a captured image is used for tracking and monitoring containers, but often fails when the code is not captured clearly. In this paper, we increase the accuracy of container code recognition using multiple views. A character-level integration method combines recognized codes from different single views to generate a new code. A decision-level integration selects the most probable results from the codes from single views and the new integrated code. The experiment confirmed that the proposed integration works successfully. The recognition from single views achieved an accuracy of around 70% for the test images collected on a working pier, whereas the proposed integration method showed an accuracy of 96%.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.57-61
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• 2015

This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduces the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept was described. CS algorithm SS-CoSaMP(Single-Space Compressive Sampling Matched Pursuit) and AMP(Approximate Message Passing) was described. Image data compressed and restored by these algorithm was compared. Calculation time of the algorithm having a low complexity is determined.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.75-81
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• 2020

Approximately 1.3 million people die from traffic accidents each year, and smartphone usage while driving is one of the main causes of such accidents. Therefore, detection of smartphone usage by drivers has become an important part of distracted driving detection. Previous studies have used single camera-based methods to collect the driver images. However, smartphone usage detection by employing a single camera can be unsuccessful if the driver occludes the phone. In this paper, we present a driver smartphone usage detection system that uses multiple cameras to collect driver images from different perspectives, and then processes these images with ensemble convolutional neural networks. The ensemble method comprises three individual convolutional neural networks with a simple voting system. Each network provides a distinct image perspective and the voting mechanism selects the final classification. Experimental results verified that the proposed method avoided the limitations observed in single camera-based methods, and achieved 98.96% accuracy on our dataset.