• Title/Summary/Keyword: Pattern-Recognition

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Driver Assistance System By the Image Based Behavior Pattern Recognition (영상기반 행동패턴 인식에 의한 운전자 보조시스템)

  • Kim, Sangwon;Kim, Jungkyu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.12
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    • pp.123-129
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    • 2014
  • In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

Galectin-1 from redlip mullet Liza haematocheilia: identification, immune responses, and functional characterization as pattern recognition receptors (PRRs) in host immune defense system

  • Chaehyeon Lim;Hyukjae Kwon;Jehee Lee
    • Fisheries and Aquatic Sciences
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    • v.25 no.11
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    • pp.559-571
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    • 2022
  • Galectins, a family of ß-galactoside-binding lectins, have emerged as soluble mediators in infected cells and pattern recognition receptors (PRRs) responsible for evoking and regulating innate immunity. The present study aimed to evaluate the role of galectin-1 in the host immune response of redlip mullet (Liza haematocheilia). We established a cDNA database for redlip mullet, and the cDNA sequence of galectin-1 (LhGal-1) was characterized. In silico analysis was performed, and the spatial and temporal expression patterns in gills and blood in response to lipopolysaccharide polyinosinic:polycytidylic acid, and Lactococcus garvieae were estimated via quantitative real-time PCR. Functional assays were conducted using recombinant protein to investigate carbohydrate binding, bacterial binding, and bacterial agglutination activity. LhGal-1 was composed of 135 amino acids. Conserved motifs (H-NPR, -N- and -W-E-R) within the carbohydrate recognition domain were found in LhGal-1. The tissue distribution revealed that the healthy stomach expressed high levels of LhGal-1. The temporal monitoring of LhGal-1 mRNA expression in the gill and blood showed its significant upregulation in response to immune challenges with different stimulants. rLhGal-1 exhibited binding activity in response to carbohydrates and bacteria. Moreover, the agglutination of rLhGal-1 against Escherichia coli was observed. Collectively, our findings suggest that LhGal-1 may function as a PRR in redlip mullet. Furthermore, LhGal-1 can be considered a significant gene to play a protective role in redlip mullet immune system.

The Development of the User-Customizable Favorites-based Smart Phone UX/UI Using Tap Pattern Similarity (탭 패턴 유사도를 이용한 사용자 맞춤형 즐겨찾기 스마트 폰 UX/UI개발)

  • Kim, Yeongbin;Kwak, Moon-Sang;Kim, Euhee
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.8
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    • pp.95-106
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    • 2014
  • In this paper, we design a smart phone UX/UI and a tap pattern recognition algorithm that can recognize tap patterns from a tapping user's fingers on the screen, and implement an application that provides user-customizable smart phones's services from the tap patterns. A user can generate a pattern by tapping the input pad several times and register it by using a smart phone's favorite program. More specifically, when the user inputs a tap pattern on the input pad, the proposed application searches a stored similar tap pattern and can run a service registered on it by measuring tap pattern similarity. Our experimental results show that the proposed method helps to guarantee the higher recognition rate and shorter input time for a variety of tap patterns.

Pattern-Recognition Receptor Signaling Initiated From Extracellular, Membrane, and Cytoplasmic Space

  • Lee, Myeong Sup;Kim, Young-Joon
    • Molecules and Cells
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    • v.23 no.1
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    • pp.1-10
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    • 2007
  • Invading pathogens are recognized by diverse germline-encoded pattern-recognition receptors (PRRs) which are distributed in three different cellular compartments: extracellular, membrane, and cytoplasmic. In mammals, the major extracellular PRRs such as complements may first encounter the invading pathogens and opsonize them for clearance by phagocytosis which is mediated by membrane-associated phagocytic receptors including complement receptors. The major membrane-associated PRRs, Toll-like receptors, recognize diverse pathogens and generate inflammatory signals to coordinate innate immune responses and shape adaptive immune responses. Furthemore, certain membrane-associated PRRs such as Dectin-1 can mediate phagocytosis and also induce inflammatory response. When these more forefront detection systems are avoided by the pathogens, cytoplasmic PRRs may play major roles. Cytoplasmic caspase-recruiting domain (CARD) helicases such as retinoic acid-inducible protein I (RIG-I)/melanoma differentiation-associated gene 5 (MDA5), mediate antiviral immunity by inducing the production of type I interferons. Certain members of nucleotide-binding oligomerization domain (NOD)-like receptors such as NALP3 present in the cytosol form inflammasomes to induce inflammatory responses upon ligand recognition. Thus, diverse families of PRRs coordinately mediate immune responses against diverse types of pathogens.

Hand Shape Recognition with Disparity Pattern of Multiple Model Images (복수 모델영상의 상위도 패턴을 이용한 손형상 인식)

  • 이칠우
    • Journal of Korea Multimedia Society
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    • v.2 no.4
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    • pp.400-408
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    • 1999
  • This paper describes a method for making the "disparity pattern" which is basis of image matching with brightness difference; called disparity, between multiple model images, and an algorithm which recognizes hand shape by utilizing the pattern in measuring the distance between a input image and model images. The virtue of the algorithm is that only simple brightness difference calculated from multiple images by managing a whole image as the fundamental processing unit is patterned in two dimensional shape and then is used in the recognition process. Consequently, this method is very useful for other recognition algorithm requiring comparison of large scale image since correlation among multiple model images is applied simultaneously in recognition process.

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The Virtual Robot Arm Control Method by EMG Pattern Recognition using the Hybrid Neural Network System (혼합형 신경회로망을 이용한 근전도 패턴 분류에 의한 가상 로봇팔 제어 방식)

  • Jung, Kyung-Kwon;Kim, Joo-Woong;Eom, Ki-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.10
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    • pp.1779-1785
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    • 2006
  • This paper presents a method of virtual robot arm control by EMG pattern recognition using the proposed hybrid system. The proposed hybrid system is composed of the LVQ and the SOFM, and the SOFM is used for the preprocessing of the LVQ. The SOFM converts the high dimensional EMG signals to 2-dimensional data. The EMG measurement system uses three surface electrodes to acquire the EMG signal from operator. Six hand gestures can be classified sufficiently by the proposed hybrid system. Experimental results are presented that show the effectiveness of the virtual robot arm control by the proposed hybrid system based classifier for the recognition of hand gestures from EMG signal patterns.

Robust Facial Expression Recognition Based on Local Directional Pattern

  • Jabid, Taskeed;Kabir, Md. Hasanul;Chae, Oksam
    • ETRI Journal
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    • v.32 no.5
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    • pp.784-794
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    • 2010
  • Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

Application of SA-SVM Incremental Algorithm in GIS PD Pattern Recognition

  • Tang, Ju;Zhuo, Ran;Wang, DiBo;Wu, JianRong;Zhang, XiaoXing
    • Journal of Electrical Engineering and Technology
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    • v.11 no.1
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    • pp.192-199
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    • 2016
  • With changes in insulated defects, the environment, and so on, new partial discharge (PD) data are highly different from the original samples. It leads to a decrease in on-line recognition rate. The UHF signal and pulse current signal of four kinds of typical artificial defect models in gas insulated switchgear (GIS) are obtained simultaneously by experiment. The relationship map of ultra-high frequency (UHF) cumulative energy and its corresponding apparent discharge of four kinds of typical artificial defect models are plotted. UHF cumulative energy and its corresponding apparent discharge are used as inputs. The support vector machine (SVM) incremental method is constructed. Examples show that the PD SVM incremental method based on simulated annealing (SA) effectively speeds up the data update rate and improves the adaptability of the classifier compared with the original method, in that the total sample is constituted by the old and new data. The PD SVM incremental method is a better pattern recognition technology for PD on-line monitoring.

A Study on Automatic Inspection Technology of Machinery Parts Based on Pattern Recognition (패턴인식에 의한 기계부품 자동검사기술에 관한 연구)

  • Cha, Bo-Nam;Roh, Chun-Su;Kang, Sung-Ki;Kim, Won-il
    • Journal of the Korean Society of Industry Convergence
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    • v.17 no.2
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    • pp.77-83
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    • 2014
  • This paper describes a new technology to develop the character recognition technology based on pattern recognition for non-contacting inspection optical lens slant or precision parts, and including external form state of lens or electronic parts for the performance verification, this development can achieve badness finding. And, establish to existing reflex data because inputting surface badness degree of scratch's standard specification condition directly, and error designed to distinguish from product more than schedule error to badness product by normalcy product within schedule extent after calculate the error comparing actuality measurement reflex data and standard reflex data mutually. Developed system to smallest 1 pixel unit though measuring is possible 1 pixel as $37{\mu}m{\times}37{\mu}m$ ($0.1369{\times}10-4mm^2$) the accuracy to $1.5{\times}10-4mm$ minutely measuring is possible performance verification and trust ability through an experiment prove.

Three-dimensional Distortion-tolerant Object Recognition using Computational Integral Imaging and Statistical Pattern Analysis (집적 영상의 복원과 통계적 패턴분석을 이용한 왜곡에 강인한 3차원 물체 인식)

  • Yeom, Seok-Won;Lee, Dong-Su;Son, Jung-Young;Kim, Shin-Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.1111-1116
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    • 2009
  • In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.