• Title/Summary/Keyword: Feature space

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A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus

  • Daoud, Mosaab
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.7.1-7.7
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    • 2020
  • In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

Analytical Decision Boundary Feature Extraction for Neural Networks (신경망을 위한 해석적 결정경계 특징추출 알고리즘)

  • 고진욱;이철희
    • Proceedings of the IEEK Conference
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    • 2000.06c
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    • pp.177-180
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    • 2000
  • Recently, a feature extraction method based on decision boundary has been proposed for neural networks. The method is based on the fact that all the features necessary to achieve the same classification accuracy as in the original space can be obtained from the vectors normal to decision boundaries. However, the normal vector was estimated numerically. resulting in inaccurate estimation and a long computational time. In this paper. we propose a new method to calculate the normal vector analytically. Experiments show that the proposed method provides a better performance.

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State estimation based on fuzzy state transition model

  • Hanazaki, Izumi;Saguchi, Shinichi
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.18-23
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    • 1993
  • In this paper, we attempt to estimate the state of a finite state system. In such system, we can observe time series data which has some significant behaviors corresponding to its system states. The behavior is characterized by feature parameters extracted from time series. Our thought is that the system output time series data is expressed as a sequence of behavior patterns which are represented by clusters in feature parameters space. An algorithm jointing fuzzy clustering to fuzzy finite state transition model is suggested.

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Feature engineering with Wavelet transform for Transient detection in KMTNet Supernova Project

  • Lee, Jae-Joon
    • The Bulletin of The Korean Astronomical Society
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    • v.42 no.2
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    • pp.64.3-64.3
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    • 2017
  • For the detection of transient sources in optical wide field surveys like KMTNet Supernova Project, difference imaging technique is commonly used. As this method produces a fair amount of false positives, it is also common to utilize machine learning algorithms to screen likely true positives. While deep learning methods such as a convolutional neural network has been successfully applied recently, its application can be limited if the size of the training sample is small. I will discuss a variation of more conventional method that adopts the wavelet transform for feature engineering and its performance.

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Linear Feature Detection of Rectangular Object Area using Edge Tracing-based Algorithm (에지 트레이싱 기법을 이용한 사각형 물체의 선형 특징점 검출)

  • 오중원;한희일
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2092-2095
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    • 2003
  • In this paper, we propose an algorithm to extract rectangular object area such 3s Data Matrix two-dimensional barcode using edge tracing-based linear feature detection. Hough transform is usually employed to detect lines of edge map. However, it requires parametric image space, and does not find the location of end points of the detected lines. Our algorithm detects end points of the detected lines using edge tracing and extracts object area using its shape information.

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Image Retrieval Using Directional Features (방향성 특징을 이용한 이미지 검색)

  • Jung, Ho-Young;Whang, Whan-Kyu
    • Journal of Industrial Technology
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    • v.20 no.B
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    • pp.207-211
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    • 2000
  • For efficient massive image retrieval, an image retrieval requires that several important objectives are satisfied, namely: automated extraction of features, efficient indexing and effective retrieval. In this work, we present a technique for extracting the 4-dimension directional feature. By directional detail, we imply strong directional activity in the horizontal, vertical and diagonal direction present in region of the image texture. This directional information also present smoothness of region. The 4-dimension feature is only indexed in the 4-D space so that complex high-dimensional indexing can be avoided.

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Speaker Identification Using GMM Based on Local Fuzzy PCA (국부 퍼지 클러스터링 PCA를 갖는 GMM을 이용한 화자 식별)

  • Lee, Ki-Yong
    • Speech Sciences
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    • v.10 no.4
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    • pp.159-166
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    • 2003
  • To reduce the high dimensionality required for training of feature vectors in speaker identification, we propose an efficient GMM based on local PCA with Fuzzy clustering. The proposed method firstly partitions the data space into several disjoint clusters by fuzzy clustering, and then performs PCA using the fuzzy covariance matrix in each cluster. Finally, the GMM for speaker is obtained from the transformed feature vectors with reduced dimension in each cluster. Compared to the conventional GMM with diagonal covariance matrix, the proposed method needs less storage and shows faster result, under the same performance.

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A Study on the Typological Analysis of the Museum Exhibition Space by Interrelationship Between Object, Human and Environment (작품-인간-환경의 관계설정에 따른 미술관 전시공간의 유형적 특성에 관한 연구)

  • 권영걸;이지영
    • Korean Institute of Interior Design Journal
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    • v.13 no.4
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    • pp.127-137
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    • 2004
  • Since 20th century, the exhibition has expanded to more diverse fields and recognized as the medium which can build network among the Art, Human and society. Space design, although developed within mutual interaction and consideration of environment factors, has been treated without those background. Therefore it is straightforward to examine the exhibition space design synthetically not limit it by the analytical elements. Assuming three main mutual interactions, object human, and environment, we have attempt the typological analysis to the museum exhibition space by studying characteristics. While the exhibition space design has been analyzed through two dimensional interpretation, on this study, we structuralize diverse discussion of the exhibition space design by relation-centered and relative analysis. Therefor we examine the characteristic of design expression through typology of both physical and behavioral feature. In the conclusion, the outcome provides insights into the relationships among object, human and environment and useful measurements to designer who outline exhibition space design.

[ $F\"{o}rstner$ ] Interest Operator in Scale Space (다축척 수치영상에서 $F\"{o}rstner$연산자의 거동)

  • Cho, Woo-Sug
    • Journal of Korean Society for Geospatial Information Science
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    • v.4 no.1 s.6
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    • pp.67-73
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    • 1996
  • The objective of this research is to investigate the behavior of the $F\"{o}rstner$ interest operator, which has been widely used for detecting distinct points in the field of digital photogrammetry and computer vision, in scale space. Considering the hugh volume of digital image utilized in digital photogrammetry, the scale space (image pyramid) approach which appears to be a solution for enhancing image processing, began to gain its attention. The investigation of the $F\"{o}rstner$ interest operator in scale space generated by the Gaussian kernel shows its behavior and feasibility for being used in practice.

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A Study on Features of Conscious Observation of Space and Search Activities for Information (공간의 의식적 주시와 정보의 탐색활동 특성에 관한 연구)

  • Kim, Jong-Ha
    • Korean Institute of Interior Design Journal
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    • v.23 no.3
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    • pp.117-124
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    • 2014
  • This study has inferred the mechanism of psychological observation activities through comparison analysis of the observation data acquired from eye-tracking and their post-estimation. The results of their analysis can be summarized as the followings. First, even though the frame of analysis has been set up so that there might not be any change to the number of the sections even with any change of consecutive observation times, the fact that the time by area decreases along with the change of consecutive observation from three times to six and nine times means that the time spent on "recognition" of space information reduces in the course that the feature of observing for space information switches from "perception to recognition". Second, the subjects moves their eyes incessantly in order to acquire space information while observing the space, when it was confirmed that there was a difference between "the space which the subjects searched for information by means of observation activities" and "that which they thought they observed that remaining in their consciousness". The appreciation of this kind of difference is very significant for the analysis of observation features. Third, the short observation (0.1 second, three times of consecutive observations) is consistent with "Ares I, intensively searched = that marked as having been observed consciously" by 60%, while the long-time observation (0.3 second, 9 times of consecutive observations) had 56%, which was relatively high, of "Area I, searched intensively ${\neq}$ that marked as having been observed consciously", which means that the observation feature seen at the activities of "consciousness : unconsciousness" and "observation : search" had some change in the course of changing from "perception to recognition".