• 제목/요약/키워드: Feature quality

검색결과 957건 처리시간 0.044초

Hybrid No-Reference Video Quality Assessment Focusing on Codec Effects

  • Liu, Xingang;Chen, Min;Wan, Tang;Yu, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권3호
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    • pp.592-606
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    • 2011
  • Currently, the development of multimedia communication has progressed so rapidly that the video program service has become a requirement for ordinary customers. The quality of experience (QoE) for the visual signal is of the fundamental importance for numerous image and video processing applications, where the goal of video quality assessment (VQA) is to automatically measure the quality of the visual signal in agreement with the human judgment of the video quality. Considering the codec effect to the video quality, in this paper an efficient non-reference (NR) VQA algorithm is proposed which estimates the video quality (VQ) only by utilizing the distorted video signal at the destination. The VQA feature vectors (FVs) which have high relationships with the subjective quality of the distorted video are investigated, and a hybrid NR VQA (HNRVQA) function is established by considering the multiple FVs. The simulation results, testing on the SDTV programming provided by VCEG Phase I, show that the proposed algorithm can represent the VQ accurately, and it can be used to replace the subjective VQA to measure the quality of the video signal automatically at the destinations.

돌출된 특징을 위한 기하 모델 단순화 방법 (Geometric Model Decimation Method for Salient Features)

  • 김수균;안성옥
    • 컴퓨터교육학회논문지
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    • 제11권4호
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    • pp.85-93
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    • 2008
  • 본 논문은 3차원 기하 모델에서 돌출된 특징 영역을 유지하며 단순화하기 위한 방법에 관한 것으로서 3차원 레인지 스캐닝 시스템으로 부터 삼각형 기하 데이터를 입력받아 기하 데이터의 각 점들에 대해 근사화 표면을 생성하고, 생성된 표면에서의 점들에 대한 곡률과 곡률 미분 값을 측정한 후, 기하 데이터의 에지에 대해 제로-클로싱을 측정하여 특정점을 찾아낸다. 특정점을 주 곡률 방향으로 연결하여 특정 선을 생성하고, 거리기반오차에 특정에지오차를 조합한 FQEM(Feature Quadric Error Metric)을 이용하여 단순화를 수행하게 된다. 본 논문에서는 제안방법의 우수성을 기존 방법과의 실험결과의 비교를 통하여 보여 준다.

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Analysis of the Visual Quality of Riverfront Skyline Through the Feature of Height and Spatial Arrangement of Tall Building

  • Puspitasari, Ayu Wandira;Kwon, Jongwook
    • Architectural research
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    • 제21권4호
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    • pp.91-98
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    • 2019
  • In modern times, numerous cities are competing to create the unique skyline adjacent to the water. Tall buildings located across the river have a great contribution to the skyline of a riverfront city and can be a precious asset for the city. Moreover, in several cities, tall buildings and their impact on the urban skyline are a matter that should be considered and regulated in urban design. Therefore, as a prominent element in a larger visual setting of the city, tall buildings should improve the visual quality of the skyline rather than diminish that quality. This research attempts to provide an objective method to analyze the visual quality of the skyline made by a group of tall buildings through their feature of heights and spatial arrangement from riverfront views. The analysis is determined by the design variables of building heights variation, heights transition, density, and spacing of a group of tall buildings. A comparative case study of tall buildings in Yeouido and Lujiazui was conducted to prove the effectiveness of the analysis. The proposed method can be used in a simple way in the quantitative approach to quantify the visual quality of the skyline. In conclusion, Yeuido's skyline is not quite interesting from the riverfront view in terms of height variation and continuity of the skyline view because they are dispersed. Conversely, Lujiazui's skyline from the riverfront vantage points has a good quality in all aspects of the feature of height and spatial arrangements of tall buildings cluster. These factors can be used for the urban designer on how proposed tall buildings within the cluster should appropriately respond to adding image on the skyline.

고차원 범주형 자료를 위한 비지도 연관성 기반 범주형 변수 선택 방법 (Association-based Unsupervised Feature Selection for High-dimensional Categorical Data)

  • 이창기;정욱
    • 품질경영학회지
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    • 제47권3호
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    • pp.537-552
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    • 2019
  • Purpose: The development of information technology makes it easy to utilize high-dimensional categorical data. In this regard, the purpose of this study is to propose a novel method to select the proper categorical variables in high-dimensional categorical data. Methods: The proposed feature selection method consists of three steps: (1) The first step defines the goodness-to-pick measure. In this paper, a categorical variable is relevant if it has relationships among other variables. According to the above definition of relevant variables, the goodness-to-pick measure calculates the normalized conditional entropy with other variables. (2) The second step finds the relevant feature subset from the original variables set. This step decides whether a variable is relevant or not. (3) The third step eliminates redundancy variables from the relevant feature subset. Results: Our experimental results showed that the proposed feature selection method generally yielded better classification performance than without feature selection in high-dimensional categorical data, especially as the number of irrelevant categorical variables increase. Besides, as the number of irrelevant categorical variables that have imbalanced categorical values is increasing, the difference in accuracy between the proposed method and the existing methods being compared increases. Conclusion: According to experimental results, we confirmed that the proposed method makes it possible to consistently produce high classification accuracy rates in high-dimensional categorical data. Therefore, the proposed method is promising to be used effectively in high-dimensional situation.

적응형 가중치 잔차 블록을 적용한 다중 블록 구조 기반의 단일 영상 초해상도 기법 (Single Image Super Resolution using Multi Grouped Block with Adaptive Weighted Residual Blocks)

  • 한현호
    • 디지털정책학회지
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    • 제3권3호
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    • pp.9-14
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    • 2024
  • 본 논문은 단일 영상 기반의 초해상도에서 결과의 품질을 개선하기 위해 적응형 가중치를 적용한 잔차 블록으로 구성된 다중 블록 구조를 이용하는 방법을 제안하였다. 딥러닝을 이용한 초해상도를 생성하는 과정에서 품질 향상을 위한 가장 중요한 요소는 특징 추출 및 적용이다. 해상도가 낮아 이미 손실된 세부사항을 복원하기 위해 다양한 특징을 추출하는 것이 최우선이지만 네트워크의 구조가 깊어지거나 복잡해지는 등의 문제가 발생하기 때문에 실제 적용에서 제한사항이 있다. 따라서 특징 추출 과정은 효율적으로 구성하고 적용 과정을 개선하여 품질을 개선하였다. 이를 위해 최초 특징 추출 이후 다중 블록 구조를 구성하였고 블록 내부에는 중첩된 잔차 블록을 구성한 뒤 적응형 가중치를 적용하였다. 또한 최종 고해상도 복원을 위해 다중 커널을 이용한 영상 재구성 과정을 적용함으로써 결과물의 품질을 향상시켰다. 평가를 위해 원본 영상 대비 PSNR과 SSIM 값을 구하였고 기존 알고리즘과 비교하여 제안하는 방법의 성능 향상을 확인하였다.

레이저 테일러드 블랭크 용접 품질 모니터링 시스템 개발 (Development of laser tailored blank weld quality monitoring system)

  • 박현성;이세헌
    • 한국레이저가공학회지
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    • 제3권2호
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    • pp.53-61
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    • 2000
  • On the laser weld production line, a slight alteration of the welding condition produces many defects. The defects are monitored in real time, in order to prevent continuous occurrence of defects, reduce the loss of material, and guarantee good quality. The measurement system is produced by using three photo-diodes for detection of the plasma and spatter signal in CO$_2$ laser welding. For high speed CO$_2$ laser welding, laser tailored welded blanks for example, on-line weld quality monitoring system was developed by using fuzzy multi-feature pattern recognition. Weld qualities were classified optimal heat input, a little low heat input, low heat input, and focus misalignment, and final weld quality were classified good and bad.

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데이터마이닝을 이용한 자동차부품 품질개선 연구 (Quality Imporovement of Auto-Parts Using Data Mining)

  • 변용완;양재경
    • 대한안전경영과학회지
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    • 제12권3호
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    • pp.333-339
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    • 2010
  • Data mining is the process of finding and analyzing data from a big database and summarizing it into useful information for a decision-making. A variety of data mining techniques have been being used for wide range of industries. One application of those is especially so for gathering meaningful information from process data in manufacturing factories for quality improvement. The purpose of this paper is to provide a methodology to improve manufacturing quality of fuel tanks which are auto-parts. The methodology is to analyse influential attributes and establish a model for optimal manufacturing condition of fuel tanks to improve the quality using decision tree, association rule, and feature selection.

지능형 홍채 인식 시스템 (An Intelligent Iris Recognition System)

  • 김재민;조성원;김수린
    • 한국지능시스템학회논문지
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    • 제14권4호
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    • pp.468-472
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    • 2004
  • 본 논문은 품질 검사, 홍채 위치 측정, 특징 추출, 검증으로 구성된 지능형 홍채 인식 시스템을 소개한다. 품질 검사를 위하여 동공 경계에 관한 국부적 통계를 사용한다. 홍채 영역을 분리하고 찾기 위하여 잘 알려진 가우시안 혼합 모형(Gaussian mixture model)을 사용한다. 특징 추출 방법은 최적화된 파형 단순화를 기초로 한다. 검증을 위해서 지능형 가변임계값을 사용한다.

Kano 모델을 기반으로 한 잠재적 고객만족 개선 지수에 관한 연구 (Development and Application of a Potential Customer Satisfaction Improvement Index based on Kano Model)

  • 임성욱;박영택
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 2010년도 춘계학술대회
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    • pp.291-309
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    • 2010
  • Customer satisfaction is an ever-growing concern of management throughout the world. To find the way to increase customer satisfaction, we must understand customer requirements. Kano distinguishes between three types of product requirements(must-be, one-dimensional, attractive requirement) which influence customer satisfaction in different ways when met. Timko has developed customer satisfaction(CS) coefficient based on Kano model. The CS coefficient is indicative of how strongly a product feature may influence satisfaction. In this paper, potential customer satisfaction improvement(PCSI) index was developed using Kano model and CS coefficient. The PCSI index represents how much a product feature can increase the degree of customer satisfaction when the product feature is fully fulfilled. In order to explain the meaning of PCSI index, a case study for cellular phones is done. It is also discussed how to use the index strategically.

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Kano 모델을 기반으로 한 잠재적 고객만족 개선지수 (Potential Customer Satisfaction Improvement Index based on Kano Model)

  • 임성욱;박영택
    • 품질경영학회지
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    • 제38권2호
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    • pp.248-260
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    • 2010
  • Customer satisfaction is an ever-growing concern of management throughout the world. To find the way to increase customer satisfaction, we must understand customer requirements. Kano distinguishes between three types of product requirements (;must-be, one-dimensional, attractive requirement) which influence customer satisfaction in different ways when met. Timko has developed customer satisfaction(CS) coefficient based on Kano model. The CS coefficient is indicative of how strongly a product feature may influence satisfaction. In this paper, potential customer satisfaction improvement(PCSI) index was proposed using Kano model and CS coefficient. The PCSI index represents how much a product feature can increase the degree of customer satisfaction when the product feature is fully fulfilled. In order to explain the meaning of PCSI index, a case study for cellular phones is done. It is also discussed how to use the index strategically.