• Title/Summary/Keyword: Segmentation model

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Lip Feature Extraction using Contrast of YCbCr (YCbCr 농도 대비를 이용한 입술특징 추출)

  • Kim, Woo-Sung;Min, Kyung-Won;Ko, Han-Seok
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.259-260
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    • 2006
  • Since audio speech recognition is affected by noise in real environment, visual speech recognition is used to support speech recognition. For the visual speech recognition, this paper suggests the extraction of lip-feature using two types of image segmentation and reduced ASM. Input images are transformed to YCbCr based images and lips are segmented using the contrast of Y/Cb/Cr between lip and face. Subsequently, lip-shape model trained by PCA is placed on segmented lip region and then lip features are extracted using ASM.

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A Study on the Apartment Choice and Housing Satisfaction by the Type of Housing Value (주거가치 유형화에 따른 아파트 선택 및 주거만족도에 관한 연구)

  • Ha, Jeung-Soon
    • Journal of the Korean housing association
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    • v.18 no.2
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    • pp.11-20
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    • 2007
  • The purpose of this study is to find the apartment Choice and Housing Satisfaction by the Housing Value Segmentation. Survey questionnaires were conducted on 1103 married women from three residential areas in Daegu. Data were analized by SPSS package program. Major findings are the following: Quality oriented type preferred environment oriented and multiple apartment. Safety investment type answered the bases of the information as of sales/model house, real estate office, oral information from relative neighbor. Ostentation negative type is dissatisfied for the present apartment were listed such as inconvenient inner structure and inner space, education environment for children, privacy protection, convenient transportation for the urban area. Convenience educational environment type is dissatisfied for the present apartment were listed such as inconvenient inner structure and inner space, anti sonic materials, education environment for children, privacy protection.

Review of Reverse Design Process for Freeform Envelope Using 3D Scanning (비정형 건축물의 외장재 제작 시공을 위한 3D 스캐닝에 의한 역 설계 프로세스 검토)

  • Kim, Sung-Jin;Park, Sung-Jin;Ryu, Hanguk
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2015.05a
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    • pp.17-18
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    • 2015
  • In manufacturing industry, image scanning technique has made enormous progress in past decades. 3D models have been also very important to continuously monitor the related spatial information for freeform buildings. The process of shape making of 3D scanning is as follows: mesh surface segmentation, NURBS surface generation, and parametric solid model generation. We will review the process and applying process. Especially in the construction industry, 3D data collection by laser scanning has become an high quality 3D models. Therefore, in this research, we have an effort to review construction of reverse design process for freeform envelope using 3D scanning. The technology enables many 3D shape engineering and design parameterization of reverse engineering in the construction site.

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Word Segmentation and POS tagging using Seq2seq Attention Model (seq2seq 주의집중 모델을 이용한 형태소 분석 및 품사 태깅)

  • Chung, Euisok;Park, Jeon-Gue
    • Annual Conference on Human and Language Technology
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    • 2016.10a
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    • pp.217-219
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    • 2016
  • 본 논문은 형태소 분석 및 품사 태깅을 위해 seq2seq 주의집중 모델을 이용하는 접근 방법에 대하여 기술한다. seq2seq 모델은 인코더와 디코더로 분할되어 있고, 일반적으로 RNN(recurrent neural network)를 기반으로 한다. 형태소 분석 및 품사 태깅을 위해 seq2seq 모델의 학습 단계에서 음절 시퀀스는 인코더의 입력으로, 각 음절에 해당하는 품사 태깅 시퀀스는 디코더의 출력으로 사용된다. 여기서 음절 시퀀스와 품사 태깅 시퀀스의 대응관계는 주의집중(attention) 모델을 통해 접근하게 된다. 본 연구는 사전 정보나 자질 정보와 같은 추가적 리소스를 배제한 end-to-end 접근 방법의 실험 결과를 제시한다. 또한, 디코딩 단계에서 빔(beam) 서치와 같은 추가적 프로세스를 배제하는 접근 방법을 취한다.

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A Study on Extracting Car License Plate Numbers Using Image Segmentation Patterns

  • Jang, Eun-Gyeom
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.10
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    • pp.87-94
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    • 2018
  • This paper proposes a method of detecting the license plates of vehicles. The proposed technology applicable to different formats of license plates detects the numbers by standardizing the images at edge points. Specifically, in accordance with the format of each license plate, the technology captures the image in the character segment, and compares it against the sample model to derive their similarity and identify the numbers. Characters with high similarities are used to form a group of candidates and to extract the final characters. Analyzing the experimental results found the similarity of the extracted characters exceeded 90%, whereas that of less identifiable numbers was markedly lower. Still, the accuracy of the extracted characters with the highest similarity was over 80%. The proposed technology is applicable to extracting the character patterns of certain formats in diverse and useful ways.

The Segmentation Hypothesis of International Capital Markets; in the Regional Stock Markets Setting

  • Ryu, Sung-Hee;Lee, Sang-Keun
    • The Korean Journal of Financial Management
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    • v.15 no.2
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    • pp.401-419
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    • 1998
  • This paper examines the international arbitrage pricing model (IAPM) in regional equity markets setting. Factor analyses are used to estimate the international common risk factors. And the cross-sectional regression analyses are used to test the validity of regional IAPMs and Chow tests are used to evaluate the integration of regional equity markets. The results of factor analyses show that the number of common factors in each regional group is seven. The cross-sectional regression results lead us not to reject that the IAPMs are regionally valid but Chow test results lead us to reject that regional equity markets are integrated.

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Development of Web-based Intelligent Recommender Systems using Advanced Data Mining Techniques (개선된 데이터 마이닝 기술에 의한 웹 기반 지능형 추천시스템 구축)

  • Kim Kyoung-Jae;Ahn Hyunchul
    • Journal of Information Technology Applications and Management
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    • v.12 no.3
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    • pp.41-56
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    • 2005
  • Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

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High Accuracy Vision-Based Positioning Method at an Intersection

  • Manh, Cuong Nguyen;Lee, Jaesung
    • Journal of information and communication convergence engineering
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    • v.16 no.2
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    • pp.114-124
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    • 2018
  • This paper illustrates a vision-based vehicle positioning method at an intersection to support the C-ITS. It removes the minor shadow that causes the merging problem by simply eliminating the fractional parts of a quotient image. In order to separate the occlusion, it firstly performs the distance transform to analyze the contents of the single foreground object to find seeds, each of which represents one vehicle. Then, it applies the watershed to find the natural border of two cars. In addition, a general vehicle model and the corresponding space estimation method are proposed. For performance evaluation, the corresponding ground truth data are read and compared with the vision-based detected data. In addition, two criteria, IOU and DEER, are defined to measure the accuracy of the extracted data. The evaluation result shows that the average value of IOU is 0.65 with the hit ratio of 97%. It also shows that the average value of DEER is 0.0467, which means the positioning error is 32.7 centimeters.

A Study on Image Segmentation for Non-uniform Image (불균등 조명 영상 분할에 관한 연구)

  • 김진숙;강진숙;차의영
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05c
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    • pp.215-218
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    • 2002
  • 영상 내에 존재하는 객체를 배경에서 분리해내는 영상분할에 대한 연구는 일반적으로 픽셀중심, 에지기반, 영역기반 그리고 모델기반의 영역에서 이루어져왔다. Active Contour 모델은 객체를 영상에서 분리하는 에지기반의 영상분할 방식이다. 전통적인 의미의 Active Contour 모델에서 사용한 그라디언트 함수 기반의 영상추출은 잡영이 많고 객체와 배경간 뚜렷한 경계가 없는 객체를 검출하는데는 그 한계를 보이고 있다. 이런 한계를 극복하고자 제안된 방법이 Mumford-Shah equation과 Lipshitz 함수를 이용한 Chan과 Vese의 Active Contour Model이다. 그런데 이 모델은 잡영이 많고 경계선이 뚜렷하지 않은 영상을 분할하는데는 효과적이나, 불균형적 조명이 있는 영상에서 객체를 분리해 내는데는 한계를 보이고 있다. 본 논문은 이러한 단점을 극복하기 위해 불균형적인 영상을 균일화하는 방법을 Chan과 Vese의 Active Contour 방식을 적용하기 전에 적용 시켜 영상 내 객체를 보다 효과적으로 추출하는 방법을 제안한다.

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Implementation of Lane Departure Warning System using Lightweight Deep Learning based on VGG-13 (VGG-13 기반의 경량화된 딥러닝 기법을 이용한 차선 이탈 경고 시스템 구현)

  • Kang, Hyunwoo
    • Journal of Korea Multimedia Society
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    • v.24 no.7
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    • pp.860-867
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    • 2021
  • Lane detection is important technology for implementing ADAS or autonomous driving. Although edge detection has been typically used for the lane detection however, false detections occur frequently. To improve this problem, a deep learning based lane detection algorithm is proposed in this paper. This algorithm is mounted on an ARM-based embedded system to implement a LDW(lane departure warning). Since the embedded environment lacks computing power, the VGG-11, a lightweight model based on VGG-13, has been proposed. In order to evaluate the performance of the LDW, the test was conducted according to the test scenario of NHTSA.