• 제목/요약/키워드: Simple detection process

검색결과 225건 처리시간 0.035초

An Enhanced Two-Stage Vehicle License Plate Detection Scheme Using Object Segmentation for Declined License Plate Detections

  • Lee, Sang-Won;Choi, Bumsuk;Kim, Yoo-Sung
    • 한국컴퓨터정보학회논문지
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    • 제26권9호
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    • pp.49-55
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    • 2021
  • 본 논문에서는 실제 도로에서 기울어진 촬영 각도로 인하여 회전된 차량 번호판을 정확하게 탐지하기 위하여 객체 세그먼테이션(object segmentation)을 이용하는 개선된 2-단계 차량 번호판 탐지 모델을 제안한다. 기존 연구에서 제안한 3-단계 차량 번호판 탐지 파이프라인 모델은 차량 번호판이 많이 기울어져 있을수록 탐지 정확도가 낮아지는 문제가 있다. 이를 해결하기 위해서 기존의 3-단계 모델에서 사각형 형태만으로 차량 후보 영역과 차량 번호판 후보 영역을 인식하는 전위 2개의 처리 단계 대신에 임의의 형태로 객체 탐지가 가능한 객체 세그먼테이션을 이용하는 하나의 단계로 대체함으로써 탐지 과정을 단순화하였으며 궁극적으로는 임의의 형태로 기울어진 차량 이미지에 대해서도 탐지 성능을 개선하였다. 기울어진 차량 번호판 이미지를 대상으로 실시한 차량 번호판 탐지 모델의 정확도 분석 실험 결과에 의하면 기존의 3-단계 차량 번호판 탐지 모델보다 제안된 2-단계 기법이 탐지 과정을 단순화하였음에도 최대 약 20%의 탐지 정확도를 개선할 수 있는 것으로 분석되었다.

전자코를 이용한 휘발성분의 분석과 식품에의 이용 (Analysis of Volatile Compounds using Electronic Nose and its Application in Food Industry)

  • 노봉수
    • 한국식품과학회지
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    • 제37권6호
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    • pp.1048-1064
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    • 2005
  • Detection of specific compounds influencing food flavor quality is not easy. Electronic nose, comprised of electronic chemical sensors with partial specificity and appropriate pattern recognition system, is capable of recognizing simple and complex volatiles. It provides fast analysis with simple and straightforward results and is best suited for quality control and process monitoring of flavor in food industry. This review examines application of electronic nose in food analysis with brief explanation of its principle. Characteristics of different sensors and sensor drift. and solutions to related problems are reviewed. Applications of electronic nose in food industry include monitoring of fermentation process and lipid oxidation, prediction of shelf life, identification of irradiated volatile compounds, discrimination of food material origin, and quality control of food and processing by principal component analysis and neural network analysis. Electronic nose could be useful for quality control in food industry when correlating analytical instrumental data with sensory evaluation results.

알츠하이머 질병의 조기진단을 위한 베타 아밀로이드의 검출 및 정량화 방법 (Detection and Quantification Method of Beta-amyloid for Alzheimer Disease Diagnosis)

  • 김관수;강재민;채철주;송기봉
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2010년도 하계학술대회 논문집
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    • pp.220-220
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    • 2010
  • The beta-amyloid protein ($A_{\beta}$) is well known for main cause of Alzheimer disease (AD). Generally, detection of $A_{\beta}$ is carried out by using fluorescent material or DNA test, but these process is long time and expensive process. Therefore, in this research, we investigated the simple diagnosis method to detect the $A_{\beta}$ by using photo-transistor.

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A New CSR-DCF Tracking Algorithm based on Faster RCNN Detection Model and CSRT Tracker for Drone Data

  • Farhodov, Xurshid;Kwon, Oh-Heum;Moon, Kwang-Seok;Kwon, Oh-Jun;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • 한국멀티미디어학회논문지
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    • 제22권12호
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    • pp.1415-1429
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    • 2019
  • Nowadays object tracking process becoming one of the most challenging task in Computer Vision filed. A CSR-DCF (channel spatial reliability-discriminative correlation filter) tracking algorithm have been proposed on recent tracking benchmark that could achieve stat-of-the-art performance where channel spatial reliability concepts to DCF tracking and provide a novel learning algorithm for its efficient and seamless integration in the filter update and the tracking process with only two simple standard features, HoGs and Color names. However, there are some cases where this method cannot track properly, like overlapping, occlusions, motion blur, changing appearance, environmental variations and so on. To overcome that kind of complications a new modified version of CSR-DCF algorithm has been proposed by integrating deep learning based object detection and CSRT tracker which implemented in OpenCV library. As an object detection model, according to the comparable result of object detection methods and by reason of high efficiency and celerity of Faster RCNN (Region-based Convolutional Neural Network) has been used, and combined with CSRT tracker, which demonstrated outstanding real-time detection and tracking performance. The results indicate that the trained object detection model integration with tracking algorithm gives better outcomes rather than using tracking algorithm or filter itself.

살모넬라균 검출을 위한 임피던스 바이오센서의 항체 고정화 방법 평가 (Evaluation of Antibody Immobilization Methods for Detection of Salmonella using Impedimetric Biosensor)

  • 김기영;문지혜;엄애선;양길모;모창연;강석원;조한근
    • Journal of Biosystems Engineering
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    • 제34권4호
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    • pp.254-259
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    • 2009
  • Conventional methods for pathogen detection and identification are labor-intensive and take several days to complete. Recently developed biosensors have shown potential for the rapid detection of foodborne pathogens. In this study, an impedimetric biosensor was developed for rapid detection of Salmonella typhimurium. To develop the biosensor, an interdigitated microelectrode (IME) was fabricated by using semiconductor fabrication process. Anti-Salmonella antibodies were immobilized based on either avidin-biotin binding or self assembled monolayer (SAM) on the surface of the IME to form an active sensing layer. To evaluate effect of antibody immobilization methods on sensitivity of the sensor, detection limit of the biosensor was analyzed with Salmonella samples innoculated in phosphate buffered saline (PBS) or food extract. The impedimetric biosensor based on SAM immobilization method produced better detection limit. The biosensor could detect 107 CFU/mL of Salmonella in pork meat extract. This method may provide a simple, rapid, and sensitive method to detect foodborne pathogens.

구조변화 통계량을 이용한 적응적 지수평활법 (Adaptive Exponential Smoothing Method Based on Structural Change Statistics)

  • 김정일;박대근;전덕빈;차경천
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2006년도 추계학술대회
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    • pp.165-168
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    • 2006
  • Exponential smoothing methods do not adapt well to unexpected changes in underlying process. Over the past few decades a number of adaptive smoothing models have been proposed which allow for the continuous adjustment of the smoothing constant value in order to provide a much earlier detection of unexpected changes. However, most of previous studies presented ad hoc procedure of adaptive forecasting without any theoretical background. In this paper, we propose a detection-adaptation procedure applied to simple and Holt's linear method. We derive level and slope change detection statistics based on Bayesian statistical theory and present distribution of the statistics by simulation method. The proposed procedure is compared with previous adaptive forecasting models using simulated data and economic time series data.

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비선형 공정의 고장검출을 위한 잔차발생알고리즘 (A residual generator for fault detection/isolation of a class of nonlinear systems)

  • 류지수;이상문;이기상;박태건
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 D
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    • pp.2230-2232
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    • 2004
  • A residual generation scheme that can be employed in the process fault detection and isolation systems for a class of nonlinear (control) systems is suggested. Although the scheme is a kind of observer scheme, the design of the observers employed for residual generation is very simple and the order of the observer is very low. In spite of the simplicity, the residual generation scheme provides the same information for the detection and isolation of the anticipated faults as the conventional multiple observer based schemes. The residuals may be structured so that fault isolation can be performed by pre-selected logic. An FDIS using the residual generation scheme is constructed and evaluated for a nonlinear DC motor system.

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Automatic face detection using chromaticity space and deformable templates

  • Lee, Kwansu;Lee, Sung-Oh;Lee, Byung-Ju;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.28.1-28
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    • 2001
  • An automatic face recognition(AFR) of individuals is a significant problem in the development of computer vision. An AFR consists of two major parts which are detection of face region and recognition process, and the overall performance of AFR is determined by each. In this paper, the face region is acquired using chromaticity space, but this face region is a simple rectangle which doesn´t consider the shape information. By applying deformable templates to the face region, we can locate the position of the eyes in images. With the face region and the eye location information, more precise face region can be extract from the image. Because processing time is critical in real-time system, we use simplified eye templates and the modified energy function for the efficiency. We can get a good detection performance in experiments.

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Repair policies of failure detection equipments and system availability

  • Na, Seongryong;Bang, Sung-Hwan
    • Communications for Statistical Applications and Methods
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    • 제29권2호
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    • pp.151-160
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    • 2022
  • The total system is composed of the main system (MS) and the failure detection equipment (FDE) which detects failures of MS. The analysis of system reliability is performed when the failure of FDE is possible. Several repair policies are considered to determine the order of repair of failed systems, which are sequential repair (SQ), priority repair (PR), independent repair (ID), and simultaneous repair (SM). The states of MS-FDE systems are represented by Markov models according to repair policies and the main purpose of this paper is to derive the system availabilities of the Markov models. Analytical solutions of the stationary equations are derived for the Markov models and the system availabilities are immediately determined using the stationary solutions. A simple illustrative example is discussed for the comparison of availability values of the repair policies considered in this paper.

반도체 공정에서의 APC 기법 및 이상감지 및 분류 시스템 (APC Technique and Fault Detection and Classification System in Semiconductor Manufacturing Process)

  • 하대근;구준모;박담대;한종훈
    • 제어로봇시스템학회논문지
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    • 제21권9호
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    • pp.875-880
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    • 2015
  • Traditional semiconductor process control has been performed through statistical process control techniques in a constant process-recipe conditions. However, the complexity of the interior of the etching apparatus plasma physics, quantitative modeling of process conditions due to the many difficult features constraints apply simple SISO control scheme. The introduction of the Advanced Process Control (APC) as a way to overcome the limits has been using the APC process control methodology run-to-run, wafer-to-wafer, or the yield of the semiconductor manufacturing process to the real-time process control, performance, it is possible to improve production. In addition, it is possible to establish a hierarchical structure of the process control made by the process control unit and associated algorithms and etching apparatus, the process unit, the overall process. In this study, the research focused on the methodology and monitoring improvements in performance needed to consider the process management of future developments in the semiconductor manufacturing process in accordance with the age of the APC analysis in real applications of the semiconductor manufacturing process and process fault diagnosis and control techniques in progress.