• 제목/요약/키워드: Extracting characteristics

검색결과 587건 처리시간 0.028초

G-Peak의 특성에 의한 피치시점검출 (The Pitch Beginning Point Extraction Using Property of G-peak)

  • 이해군
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1993년도 학술논문발표회 논문집 제12권 1호
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    • pp.259-262
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    • 1993
  • In this paper, a new pitch beginning point detection method by extracting the G-peak, is proposed. By the speech production model, the area of the first peak on a pitch interval of speech signals is emphasized. By using the above characteristics, this method have more advantages than the others for pitch beginning point detection. The defective decision caused by an impulsive noise is minimized and the pre-filtering is not necessary for this method, because the integration of signals takes place in the process.

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시설재배지 토양의 염류축적 현상과 제염방안 (Effectivess of a salt extraction technique in soils under protected cultivation)

  • 홍성구;이남호;전우정;황한철;김진태
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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    • pp.447-453
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    • 1999
  • Salt accumulation is one of themajor problems in soils under protected cultivation . Since protected cultivation does not have rainfall or excessive irrigation, salt accumulaiton inthe soils is inevitable. In this study, characteristics of salt accumulation in soil column were ivestigated, and a salt-extracting method was tested to see its effectiveness. The results showed that the concentration of salt in top soil layers increased and electrical conductivity as thesalt concentration decreased especially in the top soil layer .When extraction medium was applied.

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Comparative Analysis of Detection Algorithms for Corner and Blob Features in Image Processing

  • Xiong, Xing;Choi, Byung-Jae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제13권4호
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    • pp.284-290
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    • 2013
  • Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.

BJT의 DC 해석 용 SPICE 모델 파라미터 추출 방법에 관한 연구 (A Study on the SPICE Model Parameter Extraction Method for the BJT DC Model)

  • 이은구
    • 전기학회논문지
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    • 제58권9호
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    • pp.1769-1774
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    • 2009
  • An algorithm for extracting the BJT DC model parameter values for SPICE model is proposed. The nonlinear optimization method for analyzing the device I-V data using the Levenberg-Marquardt algorithm is proposed and the method for calculating initial conditions of model parameters to improve the convergence characteristics is proposed. The base current and collector current obtained from the proposed method shows the root mean square error of 6.04% compared with the measured data of the PNP BJT named 2SA1980.

웨이브렛 변환과 신경회로망을 이용한 SMD IC 패턴인식 (Pattern recognition of SMD IC using wavelet transform and neural network)

  • 이명길;이준신
    • 전자공학회논문지S
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    • 제34S권7호
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    • pp.102-111
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    • 1997
  • In this paper, a patern recognition method of surface mount device(SMD) IC using wavelet transform and neural network is proposed. We chose the feature parameter according to the characteristics of coefficient matrix which is obtained from four level discrete wavelet transform (DWT). These feature parameters are normalized and then used for the input vector of neural network which is capable of adapting the surroundings such as variation of illumination, arrangement of objects and translation. Experimental results show that when the same form of feature pattern, as is used for learning, is put into neural network and gained 100% rate ofrecognition irrespective of SMD IC kinds, location and variation of illumination. In the case of unused feature pattern for learning, the recognition rate is 85.9% under the similar surroundings, where as an average recognition rate is 96.87% for the case of reregulated value of illumination. Proosed method is relatively simple compared with the traditional space domain method in extracting the feature parameter and is also well suited for recognizing the pattern's class, position and existence. It can also shorten the processing tiem better than method extracting feature parameter with the use of discrete cosine transform(DCT) and adapt the surroundings such as variation of illumination, the arrangement and the translation of SMD IC.

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인삼 추출물 처리에 의한 천연 염색 면직물의 기능성 연구 (A Study on Dyeability of Cotton Fabrics using Ginseng Extracts)

  • 김월순
    • 복식문화연구
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    • 제19권2호
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    • pp.324-333
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    • 2011
  • This study was accomplished for the purpose of developing a textile processing ingredient that is harmless to the human body and environment. The research method consists of dyeing cotton textiles by extracting the dye solution from ginseng. Then, chrominance, after treatment, antibacterial ratio and deodorization ratio of cotton fabrics dyed with ginseng extracts were tested and results were examined. The research procedure involved first extracting the dye solution from the ginseng's by-product (fine roots) and then dyeing was effectuated differently according to the test samples temperature and dyeing time requirements. Brightness in all dye substances was lower in pre-mordanting. Beige color could be extracted from pre-mordanted samples. And dark orange from postmordanted samples. Color-festness was high in all samples. Most of samples show a big antibacterial ratio and deodorization ratio. Through this research it has been discovered that, when applied to textiles, Korea's ginseng extract possessed reproducibility features as a natural dye and a possibility to be used in cutting which plays a crucial role in hygienic processing. In addition, by using ginseng's by-product for dyeing processing as the dye solution, efficient application of resources and occurrences of no water waste damages were demonstrated and thus, proved to be environmentally-friendly. Specifically, through this experiment, it was found that saponin, ginseng's special characteristics, possessed excellent antibacterial odor repelling functions to clothing as well as the capability to prevent skin disease.

디지털 사진측량 처리기법에 의한 도로사면의 모니터링 정보 추출 (Extracting Information on Road Slope Monitoring by Digital Photogrammetric Processing Techniques)

  • 이진덕;연상호;이호찬
    • 한국지리정보학회지
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    • 제8권3호
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    • pp.55-64
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    • 2005
  • 본 연구는 사면의 모니터링을 위한 데이터 획득을 위하여 수치사진측량기법을 이용한 실험결과를 제시한 것이다. 근거리 디지털 영상을 도로 암반사변의 모니터링에 적용하기 위하여 수치사진 측량 워크스테이션 상에서 수치고도모형(DEM) 및 정사영상을 작성하고, 3차원 모델링 등 실제적인 사변의 형태를 시각화하였다. 이러한 수치사진측량 생성자료들은 기존 사면의 형태와 특성을 정확하게 조사, 분석하여 각종 공학적 데이터를 추출하고 사변의 DB화 및 사변의 진단과 평가를 위한 객관적이며 과학적인 자료로 활용될 수 있을 것이다.

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Comparative Study of Corner and Feature Extractors for Real-Time Object Recognition in Image Processing

  • Mohapatra, Arpita;Sarangi, Sunita;Patnaik, Srikanta;Sabut, Sukant
    • Journal of information and communication convergence engineering
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    • 제12권4호
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    • pp.263-270
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    • 2014
  • Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.

한국어 음성을 이용한 연령 분류 딥러닝 알고리즘 기술 개발 (Development of Age Classification Deep Learning Algorithm Using Korean Speech)

  • 소순원;유승민;김주영;안현준;조백환;육순현;김인영
    • 대한의용생체공학회:의공학회지
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    • 제39권2호
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    • pp.63-68
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    • 2018
  • In modern society, speech recognition technology is emerging as an important technology for identification in electronic commerce, forensics, law enforcement, and other systems. In this study, we aim to develop an age classification algorithm for extracting only MFCC(Mel Frequency Cepstral Coefficient) expressing the characteristics of speech in Korean and applying it to deep learning technology. The algorithm for extracting the 13th order MFCC from Korean data and constructing a data set, and using the artificial intelligence algorithm, deep artificial neural network, to classify males in their 20s, 30s, and 50s, and females in their 20s, 40s, and 50s. finally, our model confirmed the classification accuracy of 78.6% and 71.9% for males and females, respectively.

고속 객체 탐지를 위한 배경화면 갱신 알고리즘에 관한 연구 (A Study on the Background Image Updating Algorithm for Detecting Fast Moving Objects)

  • 박종범
    • 한국ITS학회 논문지
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    • 제15권4호
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    • pp.153-160
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    • 2016
  • 영상취득 장치를 이용한 지능화된 감시 장치의 개발 기술 또한 발전하고 있다. 비교적 고속으로 움직이는 객체를 탐지해야 하는 분야에서 무엇보다 중요한 것은 배경영상 갱신에 대한 부하를 효과적으로 줄여서 실시간적으로 갱신할 수 있어야 하는데 현재 범용 컴퓨터 능력으로는 질감 등을 특징으로 추출하는 방법 등은 대부분 연산처리의 부하 때문에 적용상의 한계가 있다. 본 논문에서는 적어도 초당 30프레임의 카메라 영상에서 주행 중인 자동차와 같이 고속으로 움직이는 객체를 탐지하는 응용영역에서 실시간으로 배경 영상을 갱신하는 알고리즘을 제시하고, 실제 입력영상에서 객체 영역을 추출하는 시험을 통해 성능을 분석하였다.