• 제목/요약/키워드: Front detection

검색결과 277건 처리시간 0.019초

RF Front End의 결함 검출을 위한 새로운 온 칩 RF BIST 구조 및 회로 설계 (New On-Chip RF BIST(Built-In Self Test) Scheme and Circuit Design for Defect Detection of RF Front End)

  • 류지열;노석호
    • 한국정보통신학회논문지
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    • 제8권2호
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    • pp.449-455
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    • 2004
  • 본 논문에서는 입력 정합(input matching) BIST(Built-In Self-Test, 자체내부검사) 회로를 이용한 RF front end(고주파 전단부)의 새로운 결함 검사방법을 제안한다. 자체내부검사 회로를 가진 고주파 전단부는 1.8GHz LNA(Low Noise Amplifier, 저 잡음 증폭기)와 이중 대칭 구조의 Gilbert 셀 믹서로 구성되어 있으며, TSMC 40.25{\mu}m$ CMOS 기술을 이용하여 설계되었다. catastrophic 결함(거폭 결함) 및 parametric 변동 (미세 결함)을 가진 고주파 전단부와 결함을 갖지 않은 고주파 전단부를 판별하기 위해 고주파 전단부의 입력 전압특성을 조사하였다. 본 검사방법에서는 DUT(Device Under Test, 검사대상이 되는 소자)와 자체내부검사회로가 동일한 칩 상에 설계되어 있기 때문에 측정할 때 단지 디지털 전압계와 고주파 전압 발생기만 필요하며, 측정이 간단하고 비용이 저렴하다는 장점이 있다.

Recognition of Car Manufacturers using Faster R-CNN and Perspective Transformation

  • Ansari, Israfil;Lee, Yeunghak;Jeong, Yunju;Shim, Jaechang
    • 한국멀티미디어학회논문지
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    • 제21권8호
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    • pp.888-896
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    • 2018
  • In this paper, we report detection and recognition of vehicle logo from images captured from street CCTV. Image data includes both the front and rear view of the vehicles. The proposed method is a two-step process which combines image preprocessing and faster region-based convolutional neural network (R-CNN) for logo recognition. Without preprocessing, faster R-CNN accuracy is high only if the image quality is good. The proposed system is focusing on street CCTV camera where image quality is different from a front facing camera. Using perspective transformation the top view images are transformed into front view images. In this system, the detection and accuracy are much higher as compared to the existing algorithm. As a result of the experiment, on day data the detection and recognition rate is improved by 2% and night data, detection rate improved by 14%.

남극 극 전선 탐지를 위한 접근법과 변동성에 대한 연구 (An Approach for the Antarctic Polar Front Detection and an Analysis for itsVariability)

  • 박진구;김현철;황지현;배덕원;조영헌
    • 대한원격탐사학회지
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    • 제34권6_2호
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    • pp.1179-1192
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    • 2018
  • 이 연구는 남빙양(Southern Ocean)에서 나타나는 주된 전선(Front)들 중에 남극 극 전선(Antarctic Polar Front; PF)을 탐지하기 위하여 위성 기반 해수면 온도(sea surface temperature)와 해수면 고도(sea surface height) 자료를 복합적으로 사용하였다. 정확한 PF 탐지를 위하여 일별 SST와 SSH 자료를 각각 기반으로 하여 베이지안 결정 이론(Bayesian decision theory)을 적용하였으며, 이를 근거로 전선/비전선의 신호를 격자 별로 분류하였다. 이후, 시공간적인 합성을 통하여 일차적인 노이즈(noise) 제거 및 지리학적 연결성을 보완하였다. 그러나 이들 과정을 수행하고도 여전히 잔존하는 일부 노이즈를 제거하기 위하여 해빙 및 연안 마스킹(masking)을 수행하였다. 또한 모폴로지 연산(morphology operation)을 통하여 지류 성분을 최대한으로 배제하고 주된 전선 성분만을 추출하였다. 최종적으로 선택된 전선 격자 들에서 PF의 특징을 나타낼 수 있도록 가장 최남단의 전선만을 선택하여 평활 스플라인(smoothing spline) 최적화 방식을 통해 선 형태의 월별 PF를 산출하였다. 산출된 PF는 기존의 연구에서 제시한 PF의 위치와 상당히 유사한 것으로 나타났으며, 특히 바닥 지형에 따라 상당 부분 결정되는 PF의 변화를 잘 모사하는 것으로 보인다. 로스해 주변(${\sim}180^{\circ}W$)과 호주 이남의 해역($120^{\circ}E-140^{\circ}E$)은 PF의 위치에 대한 계절적 변동이 높게 나타나며, 그러한 변동이 기존에 제시된 결과와 상당히 유사한 경향을 지닌다. 그러므로 이 연구에서 산출된 PF의 위치에 대한 탐지 결과가 향후 장기적 관점에서 수행될 연구에 사용될 수 있는 가치를 지닐 것으로 기대한다.

RF front-end Module for On-Line UHF Partial-discharge Monitoring System

  • Lee June Young;Kim Bok Ki
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 학술대회지
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    • pp.776-779
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    • 2004
  • A RF front-end module is designed for GIS(Gas Insulated Substation) which is employed for effective and efficient very high voltage transmission. Major advantage of the unit is improved PO detection sensitivity through minimizing the effect of surrounding interference signals, which is achieved by controlling the gain and the selection of the frequency band, for the precise detection of any UHF PO (Partial Discharge) disturbance occurred in the GIS due to some unwanted problems. For the development of the module, various switches for providing selected signal paths, wideband LNA, 3 BPF for selecting detection frequency band, and video detector are designed, fabricated and measured on 1 mm FR4 substrate with various RF components. The detection sensitivity of the unit was <-60 dBm that is sufficient to detect UHF PO signals as low as 1 pC. It is believed that the value is enough to detect the signal occurred in GIS.

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보행자 타입에 따른 보행자의 관절 점 자동 추출 알고리즘 (Auto-Detection Algorithm of Gait's Joints According to Gait's Type)

  • 곽내정;송특섭
    • 한국멀티미디어학회논문지
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    • 제21권3호
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    • pp.333-341
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    • 2018
  • In this paper, we propose an algorithm to automatically detect gait's joints. The proposed method classifies gait's types into front gait and flank gait so as to automatically detect gait's joints. And then according to classified types, the proposed applies joint extracting algorithm to input images. Firstly, we split input images into foreground image using difference images of Hue and gray-scale image of input and background one and extract gait's object. The proposed method classifies gaits into front gait and flank gait using ratio of Face's width to torso's width. Then classified gait's type, joints are detected 10 at front gait and detected 7~8 at flank gait. The proposed method is applied to the camera's input and the result shows that the proposed method automatically extracts joints.

전방 투사 인터랙티브 디스플레이를 위한 맨손 검출 (Hand Detection for Front-Projected Interactive Displays)

  • 남양희;오수진
    • 한국멀티미디어학회논문지
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    • 제10권9호
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    • pp.1135-1142
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    • 2007
  • 전방투사형 인터랙티브 디스플레이에서는 프로젝터의 빔이 사용자의 손이나 몸에도 투사되는 특성으로 인해 보편적 칼라 추져 기법을 통한 맨 손 영역의 검출이 어렵다. 본 논문에서는 원본 영상의 칼라가 카메라 영상으로 포착되기까지 칼라의 변환 관계를 분석하여 결과를 추정함으로써, 기대치와의 차이 영역 계산을 통해 손 영역을 검출하였다. 이 때, 기존 논문의 부정확한 칼라 추정을 보완하기 위해, 프로젝터와 카메라 반응 값의 칼라 채널별 간섭현상 및 투사된 프레임 내부의 밝기 오차를 룩업테이블로 모델링 하고 맨 손 영역에 대해 유동적인 밝기 차 임계치를 적용하여 정확도를 개선하였다.

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Vehicle Manufacturer Recognition using Deep Learning and Perspective Transformation

  • Ansari, Israfil;Shim, Jaechang
    • Journal of Multimedia Information System
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    • 제6권4호
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    • pp.235-238
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    • 2019
  • In real world object detection is an active research topic for understanding different objects from images. There are different models presented in past and had significant results. In this paper we are presenting vehicle logo detection using previous object detection models such as You only look once (YOLO) and Faster Region-based CNN (F-RCNN). Both the front and rear view of the vehicles were used for training and testing the proposed method. Along with deep learning an image pre-processing algorithm called perspective transformation is proposed for all the test images. Using perspective transformation, the top view images were transformed into front view images. This algorithm has higher detection rate as compared to raw images. Furthermore, YOLO model has better result as compare to F-RCNN model.

A Study of Computer Simulation of Back-and-Forth Patrol

  • Hur, Seong-Pil
    • 한국국방경영분석학회지
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    • 제14권1호
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    • pp.53-62
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    • 1988
  • A patroller is to protect a patrol area with a certain length front D by proceeding at constant speed on courses parallel to the patrol front, traveling back and forth between area boundaries and reversing course at each area boundary. Transitors enter the area uniformly distributed across the patrol front on a course perpendicular to the patrol front. Any transitor that closes the patroller to within his sweep radius R is detected. This paper use plane trigonometry to derive the theoretical probailities of detection and develop a Monte Carlo computer simulation Model.

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A Study of Computer Simulation of Back-and-Forth Patrol

  • Hur, Seong-Pil
    • 한국국방경영분석학회지
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    • 제13권2호
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    • pp.53-62
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    • 1987
  • A patroller is to protect a patrol area with a certain length front D by proceeding at constant speed on courses parallel to the patrol front, traveling back and forth between area boundaries and reversing course at each area boundary. Transitors enter the area uniformly distributed across the patrol front on a course perpendicular to the patrol front. Any transitor that closes the patroller to within his sweep radius R is detected. This paper use plane trigonometry to derive the theoretical probailities of detection and develop a Monte Carlo computer simulation Model.

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A Compact Ka-Band Doppler Radar Sensor for Remote Human Vital Signal Detection

  • Han, Janghoon;Kim, Jeong-Geun;Hong, Songcheol
    • Journal of electromagnetic engineering and science
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    • 제12권4호
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    • pp.234-239
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    • 2012
  • This paper presents a compact K-band Doppler radar sensor for human vital signal detection that uses a radar configuration with only single coupler. The proposed radar front-end configuration can reduce the chip size and the additional RF power loss. The radar front-end IC is composed of a Lange coupler, VCO, and single balanced mixer. The oscillation frequency of the VCO is from 27.3 to 27.8 GHz. The phase noise of the VCO is -91.2 dBc/Hz at a 1 MHz offset frequency, and the output power is -4.8 dBm. The conversion gain of the mixer is about 11 dB. The chip size is $0.89{\times}1.47mm^2$. The compact Ka-band Doppler radar system was developed in order to demonstrate remote human vital signal detection. The radar system consists of a Ka-band Doppler radar module with a $2{\times}2$ patch array antenna, baseband signal conditioning block, DAQ system, and signal processing program. The front-end module size is $2.5{\times}2.5cm^2$. The proposed radar sensor can properly capture a human heartbeat and respiration rate at the distance of 50 cm.