• 제목/요약/키워드: Vector Generation

검색결과 548건 처리시간 0.029초

실사형 캐리커처 생성을 위한 형태 정보 추출 및 음영 함성 (Appearance Information Extraction and Shading for Realistic Caricature Generation)

  • 박연출;오해석
    • 정보처리학회논문지B
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    • 제11B권3호
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    • pp.257-266
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    • 2004
  • 본 논문은 윤곽선만을 추출하여 캐리커처를 생성하던 기존의 시스템과 달리 음영을 윤곽선과 합성하여 캐리커처를 생성하는 캐리커처 생성 시스템을 제안한다. 이 방식을 사용할 경우 얼굴의 텍스추어 정보까지 생성시 고려하기 때문에 좀 더 실사형에 근접한 캐리커처를 생성할 수 있다. 본 논문에서 제안하는 시스템은 벡터를 기만으로 하기 때문에 사이즈에 제한 없이 자유로운 변형이 가능할 뿐만 아니라 2D 캐릭터에 자유로운 표정을 적용하는 데에도 쉽게 적용이 가능하다. 또, 벡터의 특징으로 인해 모바일 상에서도 적은 용량으로 이용 가능하다. 본 논문은 벡터 형태의 캐리커처를 생성하는 방법과 음영을 제작 및 합성하는 방법을 함께 제시한다.

조합회로에 대한 게이트 지연 검사 패턴 생성기의 속도 향상에 관한 연구 (A Study on Speed Improvement of Gate Delay Test Generator for Combinational Circuits)

  • 박승용;김규철
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.723-726
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    • 1998
  • Fault dropping is a very important part of test generation process. It is used to reduce test generation time. Test generation systems use fault simulation for the purpose of fault dropping by identifying detectable faults with generated test patterns. Two kinds of delay fault model is used in practice, path delay fault model and gate delay fault model. In this paper we propose an efficient method for gate delay test generation which shares second test vector.

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보조정보의 움직임 벡터를 이용한 분산 비디오 코딩에서 H.264/AVC로의 트랜스코딩 (Transcoding from Distributed Video Coding to H.264/AVC Based on Motion Vectors of Side Information)

  • 민경연;유성은;심동규;전병우
    • 방송공학회논문지
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    • 제16권1호
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    • pp.108-122
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    • 2011
  • 본 논문은 저복잡도 및 고효율 분산 비디오 코딩에서 H.264/AVC로의 변환을 위한 트랜스코딩 방법을 제안한다. 제안한 방법은 낮은 복잡도로 높은 부호화 성능을 유지하기 위하여, 보조정보 생성을 위하여 측정된 움직임 벡터를 Wyner-Ziv (WZ) 프레임뿐만 아니라 키 프레임에서도 적용하여 부화화를 수행한다. 보조정보 생성을 위하여 측정된 움직임 벡터는 키 프레임에서 이전의 키 프레임으로의 움직임 추정에 의해 결정된 움직임 벡터임으로, 이 움직임 벡터를 이용하여 인트라 키 프레임을 예측 프레임으로 변환압축하는 방법을 제안한다. 또한, 제안한 방법은 두 예측 움직임 벡터를 기반으로 측정된 두 움직임 벡터 중, 비트율-왜곡 최적화를 수행하여 최적의 움직임 벡터를 선택한다. 보조정보의 움직임 벡터는 보조정보를 생성하기 위하여 수행된 움직임 추정을 통하여 측정된 움직임 벡터임으로, 적은 탐색 영역을 적용하여도 높은 부호화 효율을 얻을 수 있다. 따라서, 제안한 방법은 예측 움직임 벡터와 보조정보 기반의 예측 움직임 벡터로 적용하여 적은 탐색 영역에서 움직임 추정을 수행함으로써, 저복잡도로 높은 부호화 효율을 가질 수 있다. 실험결과는 기존 변환 방법과 대비하여, 트랜스코더의 복잡도가 2.82%로 감소하고 비트율 성능은 23.06% 상향되었다.

Efficient Hybrid Carrier Based Space Vector Modulation for a Cascaded Multilevel Inverter

  • Govindaraju, C.;Baskaran, K.
    • Journal of Power Electronics
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    • 제10권3호
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    • pp.277-284
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    • 2010
  • This paper presents a novel hybrid carrier based space vector modulation for cascaded multilevel inverters. The proposed technique inherits the properties of carrier based space vector modulation and the fundamental frequency modulation strategy. The main characteristic of this modulation are the reduction of power loss, and improved harmonic performance. The carrier based space vector modulation algorithm is implemented with a TMS320F2407 digital signal processor. A Xilinx Complex Programmable Logic Device is used to develop the hybrid PWM control algorithm and it is integrated with a digital signal processor for hybrid carrier based space vector PWM generation. The inverter offers less weighted total harmonic distortion and it operates with equal electrostatic and electromagnetic stress among the power devices. The feasibility of the proposed technique is verified by spectral analysis, simulation, and experimental results.

동적으로 출력 뉴런을 생성하는 경쟁 학습 신경회로망 (Competitive Learning Neural Network with Dynamic Output Neuron Generation)

  • 김종완;안제성;김종상;이흥호;조성원
    • 전자공학회논문지B
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    • 제31B권9호
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    • pp.133-141
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    • 1994
  • Conventional competitive learning algorithms compute the Euclidien distance to determine the winner neuron out of all predetermined output neurons. In such cases, there is a drawback that the performence of the learning algorithm depends on the initial reference(=weight) vectors. In this paper, we propose a new competitive learning algorithm that dynamically generates output neurons. The proposed method generates output neurons by dynamically changing the class thresholds for all output neurons. We compute the similarity between the input vector and the reference vector of each output neuron generated. If the two are similar, the reference vector is adjusted to make it still more like the input vector. Otherwise, the input vector is designated as the reference vector of a new outputneuron. Since the reference vectors of output neurons are dynamically assigned according to input pattern distribution, the proposed method gets around the phenomenon that learning is early determined due to redundant output neurons. Experiments using speech data have shown the proposed method to be superior to existint methods.

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Power Quality Disturbances Identification Method Based on Novel Hybrid Kernel Function

  • Zhao, Liquan;Gai, Meijiao
    • Journal of Information Processing Systems
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    • 제15권2호
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    • pp.422-432
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    • 2019
  • A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

병렬 컴퓨팅 시스템에서 LLVM 응용 연구 (Study on LLVM application in Parallel Computing System)

  • 조중석;조두산;김용연
    • 문화기술의 융합
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    • 제5권1호
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    • pp.395-399
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    • 2019
  • 다양한 병렬 컴퓨팅 시스템을 지원하기 위해서는 LLVM IR을 벡터/행렬을 보다 효과적으로 지원할 수 있도록 확장하는 것과 LLVM IR을 machine code로 바꾸어 주는 부분을 새로운 알고리즘으로 설계하여 구현하면 된다. IR 예제에서 보았듯이 기본적으로 RISC 명령어로 구성되어 있기 때문에 RISC 명령어 생성은 자연스럽게 생성되며, 벡터 또한 현재 지원가능한데 행렬 명령어는 지원되지 못하고 있다. 벡터/행렬을 보다 강력하게 지원하기 위한 새로운 IR 구조, 명령어 생성 알고리즘 및 관련 부분의 확장이 필요하다. 이를 위해 LLVM IR의 각 명령어를 (벡터/행렬을 위한) target architecture의 적당한 명령어로 mapping을 해주는 부분 (instruction selection 알고리즘)이 중요하다. LLVM IR 명령어의 의미를 파악하고, target architecture의 각 명령어 의미와 syntax를 비교하여, 패턴이 일치하는 명령어를 선택하여 mapping을 효율적으로 해줘야 한다.

Few-Shot Image Synthesis using Noise-Based Deep Conditional Generative Adversarial Nets

  • Msiska, Finlyson Mwadambo;Hassan, Ammar Ul;Choi, Jaeyoung;Yoo, Jaewon
    • 스마트미디어저널
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    • 제10권1호
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    • pp.79-87
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    • 2021
  • In recent years research on automatic font generation with machine learning mainly focus on using transformation-based methods, in comparison, generative model-based methods of font generation have received less attention. Transformation-based methods learn a mapping of the transformations from an existing input to a target. This makes them ambiguous because in some cases a single input reference may correspond to multiple possible outputs. In this work, we focus on font generation using the generative model-based methods which learn the buildup of the characters from noise-to-image. We propose a novel way to train a conditional generative deep neural model so that we can achieve font style control on the generated font images. Our research demonstrates how to generate new font images conditioned on both character class labels and character style labels when using the generative model-based methods. We achieve this by introducing a modified generator network which is given inputs noise, character class, and style, which help us to calculate losses separately for the character class labels and character style labels. We show that adding the character style vector on top of the character class vector separately gives the model rich information about the font and enables us to explicitly specify not only the character class but also the character style that we want the model to generate.

Induced Pluripotent Stem Cell Generation using Nonviral Vector

  • Park, Si-Jun;Shin, Mi-Jung;Seo, Byoung-Boo;Park, Hum-Dai;Yoon, Du-Hak;Ryoo, Zae-Young
    • Reproductive and Developmental Biology
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    • 제35권4호
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    • pp.449-455
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    • 2011
  • Induced pluripotent stem (iPS) cells have been generated from mouse and human somatic cells by etopic expression of transcription factors. iPS cells are indistinguishable from ES cells in terms of morphology and stem cell marker expression. Moreover, mouse iPS cells give rise to chimeric mice that are competent for germline transmission. However, mice derived from iPS cells often develop tumors. Furthermore, the low efficiency of iPS cell generation is a big disadvantage for mechanistic studies. Nonviral plasmid.based vectors are free of many of the drawbacks that constrain viral vectors. The histone deacetylase inhibitor valproic acid (VPA) has been shown to improve the efficiency of mouse and human iPS cell generation, and vitamin C (Vc) accelerates gene expression changes and establishment of the fully reprogrammed state. The MEK inhibitor PD0325901 (Stemgent) has been shown to increase the efficiency of the reprogramming of human primary fibroblasts into iPS cells. In this report, we described the generation of mouse iPS cells devoid of exogenous DNA by the simple transient transfection of a nonviral vector carrying 2A-peptide-linked reprogramming factors. We used VPA, Vc, and the MEK inhibitor PD0325901 to increase the reprogramming efficiency. The reprogrammed somatic cells expressed pluripotency markers and formed EBs.

A FACE IMAGE GENERATION SYSTEM FOR TRANSFORMING THREE DIMENSIONS OF HIGHER-ORDER IMPRESSION

  • Ishi, Hanae;Sakuta, Yuiko;Akamatsu, Shigeru;Gyoba, Jiro
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.703-708
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    • 2009
  • The present paper describes the application of an improved impression transfer vector method (Sakurai et al., 2007) to transform the three basic dimensions (Evaluation, Activity, and Potency) of higher-order impression. First, a set of shapes and surface textures of faces was represented by multi-dimensional vectors. Second, the variation among faces was coded in reduced parameters derived by applying principal component analysis. Third, a facial attribute along a given impression dimension was analyzed to select discriminative parameters from among principal components with higher sensitivity to impressions, and obtain an impression transfer vector. Finally, the parametric coordinates were changed by adding or subtracting the impression transfer vector and the image was manipulated so that its facial appearance clearly exhibits the transformed impression. A psychological rating experiment confirmed that the impression transfer vector modulated three dimensions of higher-order impression. We discussed the versatility of the impression transfer vector method.

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