• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.69-71
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• 2023

본 논문은 YOLO 기반 모델의 철도 시스템 내 선로 고정장치 탐지 성능을 비교하고 분석한다. 여기서 철도 시스템은 열차가 주행하기 위한 선로, 침목, 패스너 등의 구성요소를 포함한다. 침목은 지반과 직접적으로 연결되며, 선로를 지반 위에 안정적으로 지지하고 궤간을 정확하게 유지하는 역할을 한다. 또한, 패스너는 선로를 침목에 단단히 고정시키는 역할을 한다. 이러한 선로 고정장치의 부재는 인명 사고로 이어질 수 있어 지속적인 관리와 유지 보수가 필수적이다. 본 논문에서는 철도 시스템의 선로 고정장치 탐지를 위해 YOLO V5 및 V8 딥러닝 모델의 적용 가능성을 실험적으로 접근하며, 두 모델의 탐지 성능을 비교한다. 실험 결과, YOLO V8 및 V5 모델은 모두 뛰어난 성능을 보이는데, 특히 YOLO V8 모델이 더욱 우수한 성능을 보인다. 이로써 YOLO 알고리즘은 선로 고정장치 탐지에 적합하다는 것을 증명한다. 그러나 일부 False Positive Sample이 관측되었음을 확인하고, 이로부터 모델 성능의 개선이 필요하다는 결론을 도출하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.515-523
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• 2021

An integrated underground spatial map consists of underground facilities, underground structures, and ground information, and is periodically updated. In this paper, we design and implement a system for detecting and extracting only changed ground objects to shorten the map update speed. To find the changed objects, all the objects are compared, which are included in the newly input map and the reference map in the integrated map. Since the entire process of comparing objects and generating results is classified by function, the implemented system is composed of several modules such as object comparer, changed object detector, history data manager, changed object extractor, changed type classifier, and changed object saver. We use two metrics: detection rate and extraction rate, to evaluate the performance of the system. As a result of applying the system to boreholes, ground wells, soil layers, and rock floors in Pyeongtaek, 100% of inserted, deleted, and updated objects in each layer are detected. In addition, it provides the advantage of ensuring the up-to-dateness of the reference map by downloading it whenever maps are compared. In the future, additional research is needed to confirm the stability and effectiveness of the developed system using various data to apply it to the field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1990.10a
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• pp.23-27
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• 1990

A new signal processing system for real time displacement measurement in sinusoidal phase modulating interferometry is described. Although sinusoidal phase modulating interferometry is effective in measuring with high accuracy the displacement of an object, conventional signal processing takes a long time. In this method, detection of the object's displacement is easily achieved by sampling the interference signal at those times that satisfy certain conditions and by processing the sampled signals with electric circuits in real time. The delay time of this signal processing system is < 45${\mu}$s. Specially in this paper we describe all electronic circuit and optical system design

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.395-401
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• 1993

The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurement of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easiliy illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is () in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed qutomatic inspection system can be applied in real situation.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1991.10a
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• pp.33-37
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• 1991

A now signal precessing system for real time displacement measurement in sinusoidal phase modulating interferometry is described. Although sinusoidal phase modulating interferometry is effective in measuring with high accuracy the displacement of an object, conventional signal processing takes along time. In this method, detection of the object's displacement is easily achieved by sampling the interference signal at those times that satisfy certain conditions and by processing the sampled signals with electric circuits in real time. the delay time of this signal processing system is < 45 $\mu$s. Specially in this paper we describe all electronic circuit and optical system design

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.72-79
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• 1995

The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurment of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easily illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is 0 in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed automatic inspection system can be applied in real situation.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2449-2451
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• 2001

The purpose of this paper is to develop image inspection system endows an automatic operating and measuring that the moment values are invariant with respect to variable object size and rotation. In this paper, using these moment feature vector with Hu's 7 invariant moment is also given. The characteristics of section which is applied in the mechanics used moment descriptor of invariant moment detection algorithm for image inspection system. Corresponding rates between 94% and 96% have archived for all object tested.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.320-328
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• 2021

As the number of visually impaired people steadily increases, interest in independent walking is also increasing. However, there are various inconveniences in the independent walking of the visually impaired at present, reducing the quality of life of the visually impaired. The white cane, which is an existing walking aid for the visually impaired, has difficulty in recognizing upper obstacles and obstacles outside the effective distance. In addition, it is inconvenient to cross the street because the sound signal to help the visually impaired cross the crosswalk is lacking or damaged. These factors make it difficult for the visually impaired to walk independently. Therefore, we propose the design of an embedded system that provides traffic light recognition through object recognition technology, voice guidance using TTS, and upper obstacle recognition through ultrasonic sensors so that blind people can realize safe and high-quality independent walking.