• 제목/요약/키워드: bio-recognition

검색결과 229건 처리시간 0.026초

TELE-OPERATIVE SYSTEM FOR BIOPRODUCTION - REMOTE LOCAL IMAGE PROCESSING FOR OBJECT IDENTIFICATION -

  • Kim, S. C.;H. Hwang;J. E. Son;Park, D. Y.
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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    • pp.300-306
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    • 2000
  • This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.

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BIT 표기법을 활용한 한국어 개체명 인식 (Korean Named Entity Recognition Using BIT Representation)

  • 윤호;김창현;천민아;박호민;남궁영;최민석;김재균;김재훈
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2019년도 제31회 한글 및 한국어 정보처리 학술대회
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    • pp.190-194
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    • 2019
  • 개체명 인식이란 주어진 문서에서 개체명의 범위를 찾고 개체명을 분류하는 것이다. 최근 많은 연구는 신경망 모델을 이용하며 하나 이상의 단어로 구성된 개체명을 BIO 표기법으로 표현한다. BIO 표기법은 개체명이 시작되는 단어의 표지에 B(Beginning)-를 붙이고, 개체명에 포함된 그 외의 단어의 표지에는 I(Inside)-를 붙이며, 개체명과 개체명 사이의 모든 단어의 표지를 O로 간주하는 방법이다. BIO 표기법으로 표현된 말뭉치는 O 표지가 90% 이상을 차지하므로 O 표지에 대한 혼잡도가 높아지는 문제와 불균형 학습 문제가 발생된다. 본 논문에서는 BIO 표기법 대신에 BIT 표기법을 제안한다. BIT 표기법이란 BIO 표기법에서 O 표지를 T(Tag) 표지로 변환하는 방법이며 본 논문에서 T 표지는 품사 표지를 나타낸다. 실험을 통해서 BIT 표기법이 거의 모든 경우에 성능이 향상됨을 확인할 수 있었다.

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로봇 착유시스템의 3차원 유두위치인식을 위한 스테레오비젼 시스템 (A Stereo-Vision System for 3D Position Recognition of Cow Teats on Robot Milking System)

  • 김웅;민병로;이대원
    • Journal of Biosystems Engineering
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    • 제32권1호
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    • pp.44-49
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    • 2007
  • A stereo vision system was developed for robot milking system (RMS) using two monochromatic cameras. An algorithm for inverse perspective transformation was developed for the 3-D information acquisition of all teats. To verify performance of the algorithm in the stereo vision system, indoor tests were carried out using a test-board and model teats. A real cow and a model cow were used to measure distance errors. The maximum distance errors of test-board, model teats and real teats were 0.5 mm, 4.9 mm and 6 mm, respectively. The average distance errors of model teats and real teats were 2.9 mm and 4.43 mm, respectively. Therefore, it was concluded that this algorithm was sufficient for the RMS to be applied.

바이오센서 (Biosensors: a review)

  • 황교선;김상경;김태송
    • 센서학회지
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    • 제18권4호
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    • pp.251-262
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    • 2009
  • Biosensors exploit the specific binding between recognition molecule on the biosensor surface and target molecule in analyte and are used in the detection of specific biomolecules such as protein, DNA, cell, virus, etc., with a view towards developing analytical devices. Recently, application field of biosensors have been expanding from diagnosis to biodefense because they can basically serve as high performance devices. This review describes the basic information of biosensors including definition, classification, and operational principle. Moreover, we introduce micro/nano technology-based biosensors with better detection performance than traditional method and their application examples.

소산파의 복굴절을 이용한 광 도파관 센서 (Optical waveguide sensors using optical birefringence of evanescent fields)

  • Son, K.S.;Lee, H.Y.;Kim, W.K.;Lee, S.S.;Park, S.S.;Kwon, S.W.;Lee, E.C.;Park, J.W.;Ju, H.
    • 한국광학회:학술대회논문집
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    • 한국광학회 2008년도 하계학술발표회 논문집
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    • pp.309-310
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    • 2008
  • Polymer optical waveguides are fabricated with high-index materials deposited to strengthen exciations of evanescent field whose birefringence is utilized for optical sensing. Optical sensing properties are examined as a function of time, using different types of analyte solutions to extract noise-free signal induced by evanescent field birefringence. It is observed that sensing signal can be free of initial noise that may obscure real signal recognition, when glycerol is used for sensing characterization, due to slow accumulation process following adsorption of analyte material onto the sensing surface of the waveguide.

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D-Tag를 이용한 한국어 개체명 인식 (Korean Named Entity Recognition using D-Tag)

  • 김은수;도수종;박천음
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2022년도 제34회 한글 및 한국어 정보처리 학술대회
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    • pp.35-40
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    • 2022
  • 본 논문에서는 시퀀스 레이블링 문제(sequence labeling problem)인 개체명 인식에 사용할 새로운 태깅 포맷인 Delimiter tag (D-tag)를 소개한다. 시퀀스 레이블링 문제에서 사용하는 BIO-tag 포맷은 개체명 레이블을 B (beginning)와 I (inside) 의미의 레이블로 확장하여 타겟 클래스의 수가 2배 증가한다. 또한 BIO-tag 포맷을 사용할 경우, 모델이 B와 I 를 잘못 분류하는 문제가 발생하며, 레이블 수가 많은 세부 분류 개체명의 경우에는 label confusion을 야기한다. 본 논문에서 제안한 D-tag 포맷은 타겟 클래스의 수를 증가시키지 않기 때문에 앞서 언급한 문제를 해결할 수 있다. 실험 결과, D-tag를 사용하여 학습한 모델이 BIO-tag를 사용한 경우보다 더 좋은 성능을 보여, 유망함을 확인하였다.

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POSITION RECOGNITION AND QUALITY EVALUATION OF TOBACCO LEAVES VIA COLOR COMPUTER VISION

  • Lee, C. H.;H. Hwang
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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    • pp.569-577
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    • 2000
  • The position of tobacco leaves is affluence to the quality. To evaluate its quality, sample leaves was collected according to the position of attachment. In Korea, the position was divided into four classes such as high, middle, low and inside positioned leaves. Until now, the grade of standard sample was determined by human expert from korea ginseng and tobacco company. Many research were done by the chemical and spectrum analysis using NIR and computer vision. The grade of tobacco leaves mainly classified into 5 grades according to the attached position and its chemical composition. In high and low positioned leaves shows a low level grade under grade 3. Generally, inside and medium positioned leaf has a high level grade. This is the basic research to develop a real time tobacco leaves grading system combined with portable NIR spectrum analysis system. However, this research just deals with position recognition and grading using the color machine vision. The RGB color information was converted to HSI image format and the sample was all investigated using the bundle of tobacco leaves. Quality grade and position recognition was performed through well known general error back propagation neural network. Finally, the relationship about attached leaf position and its grade was analyzed.

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딥러닝 기반의 얼굴영상에서 표정 검출에 관한 연구 (Detection of Face Expression Based on Deep Learning)

  • 원철호;이법기
    • 한국멀티미디어학회논문지
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    • 제21권8호
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    • pp.917-924
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    • 2018
  • Recently, researches using LBP and SVM have been performed as one of the image - based methods for facial emotion recognition. LBP, introduced by Ojala et al., is widely used in the field of image recognition due to its high discrimination of objects, robustness to illumination change, and simple operation. In addition, CS(Center-Symmetric)-LBP was used as a modified form of LBP, which is widely used for face recognition. In this paper, we propose a method to detect four facial expressions such as expressionless, happiness, surprise, and anger using deep neural network. The validity of the proposed method is verified using accuracy. Based on the existing LBP feature parameters, it was confirmed that the method using the deep neural network is superior to the method using the Adaboost and SVM classifier.

홍채 인식을 위한 동공 중심점 탐색 알고리즘에 관한 연구 (The Study on Searching Algorithm of the center of Pupil for the Iris Recognition)

  • 조민환;허정연
    • 한국컴퓨터정보학회논문지
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    • 제11권1호
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    • pp.19-25
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    • 2006
  • 홍채인식은 개인의 홍채 패턴을 이용한 인식시스템으로 정보보안 분야나 개인 인증에 최고의 인증시스템중 하나로 알려져 있다. 홍채 인식을 위해 가장 먼저 해결해야하는 문제는 동공중심점탐색 이 매우 중요하다. 지금까지 많은 탐색 알고리즘들이 개발되었으나 대부분 처리시간이 매우 많이 소요된다. 본 논문에서는 새로운 동공 중심점 탐색 방법을 제시하고, Hough 변환을 이용한 방법과 비교하였다. 그 결과 120개의 이미지를 대상으로 실험한 결과 약 30%의 처리 속도 개선의 결과를 얻었다.

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