• 제목/요약/키워드: Feature suppression

검색결과 63건 처리시간 0.032초

저전력, 고속데이터 의존 프리차지 억제 DFF (Low power and high speed Data-dependent Precharge Suppression DFF)

  • 채관엽;기훈재;황인철;김수원
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 추계종합학술대회 논문집
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    • pp.240-243
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    • 1999
  • This paper presents a data-dependent precharge suppression(DPS) D-flip-flop(DFF) with precharge suppression scheme according to data-transition probability The main feature of the DPS DFF is that precharge is suppressed when there is no data transition. The proposed DPS DFF consumes less power than the conventional Yuan-Svensson's true single phase clocking(TSPC) DFF when the data-transition probability is low. The simulation result shows that the power consumption is reduced by 42.2 % when the data-transition probability is 30%.

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기준 특징형상에 기반한 셀 분해 및 특징형상 인식에 관한 연구 (Reference Feature Based Cell Decomposition and Form Feature Recognition)

  • 김재현;박정환
    • 한국CDE학회논문집
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    • 제12권4호
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    • pp.245-254
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    • 2007
  • This research proposed feature extraction algorithms as an input of STEP Ap214 data, and feature parameterization process to simplify further design change and maintenance. The procedure starts with suppression of blend faces of an input solid model to generate its simplified model, where both constant and variable-radius blends are considered. Most existing cell decomposition algorithms utilize concave edges, and they usually require complex procedures and computing time in recomposing the cells. The proposed algorithm using reference features, however, was found to be more efficient through testing with a few sample cases. In addition, the algorithm is able to recognize depression features, which is another strong point compared to the existing cell decomposition approaches. The proposed algorithm was implemented on a commercial CAD system and tested with selected industrial product models, along with parameterization of recognized features for further design change.

특징형상기반 솔리드 모델의 간략화 방법에 관한 연구 (A Simplification Method for Feature-based Solid Models)

  • 손태근;신동평;명대광;류철호;이상헌;이건우
    • 한국CDE학회논문집
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    • 제15권3호
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    • pp.243-252
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    • 2010
  • This paper describes a new practical simplification method for feature-based solid models. In this approach, a solid model created using feature modeling operations is first simplified by the suppression of detailed features, and then, if necessary, the model is converted to a surface model to facilitate its modification. Finally, the simplified surface model is delivered to analysis packages. The algorithm was implemented based on CATIA V.5 and applied to mid-surface generation of plastic parts for structural analysis to prove the validity and usefulness.

A method based on Multi-Convolution layers Joint and Generative Adversarial Networks for Vehicle Detection

  • Han, Guang;Su, Jinpeng;Zhang, Chengwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.1795-1811
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    • 2019
  • In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

에지 검출에 의한 차량 식별 (Identification of Vehicle Using Edge Detection)

  • 신성윤;김도관;이창우;이현창;이태욱;박기홍
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2016년도 추계학술대회
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    • pp.382-383
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    • 2016
  • 영상의 캐니 에지 검출은 영상의 가우시안 필터, 기울기(gradient)의 계산, 비최대억제법(Non-maximum suppression), 그리고 이력 임계값(Hypothesis Thresholding)의 4가지로 구성된다. 특징은 에지 영상에서 얻어진 차체, 창문들, 그리고 바퀴들 사이의 비율이 된다. 차량의 이러한 특징이 되는 비율들은 차종마다 각기 다르다. 우리는 여기서 소형 차량에만 본 알고리즘을 적용하여 식별하였다.

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메모리 사용률을 개선한 SURF 알고리즘 특징점 추출기의 하드웨어 가속기 설계 (An Implementation of a Feature Extraction Hardware Accelerator based on Memory Usage Improvement SURF Algorithm)

  • 정창민;곽재창;이광엽
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2013년도 추계학술대회
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    • pp.77-80
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    • 2013
  • SURF 알고리즘은 영상의 특징점 검출 및 서술자를 생성하는 알고리즘으로 크기와 회전, 조명 및 시점 등의 환경 변화에 강인한 특징을 가지고 있다. 이러한 특징 때문에 객체 인식, 파노라마 이미지, 3차원 영상 복원 등 영상처리 분야에서 많이 사용되고 있다. 하지만 SURF 알고리즘과 같은 대부분의 인식 알고리즘은 많은 양의 연산을 필요로 하기 때문에 실시간 구현이 어렵다. 본 논문은 SURF의 메모리 접근 횟수와 메모리 사용량을 분석하여 효율적인 메모리를 설계함으로써 메모리 접근 횟수와 메모리 사용량을 최소화하여 실시간 구현이 가능하도록 설계하였다.

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청각 계통에서의 음성신호처리 (Speech signal processing in the auditory system)

  • 이재혁;심재성;백승화;박상희
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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    • pp.680-683
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    • 1987
  • The speech signal processing in the auditory system can be analysized based on two representations : Average discharge rate and Temporal discharge pattern. But the average discharge rate representation is restricted by the narrow dynamic range because of the rate saturation and the two tone suppression phenomena, and the temporal discharge pattern representation needs a sophisticate frequency analysis and synchrony measure. In this paper, a simple representation is proposed : using a model considering the interaction of Cochlear fluid-BM movement and a haircell model, the feature of speech signals (formant frequency and pitch of vowels) is easily estimated in the Average Synchronized Rate.

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RESEARCH ON SENTIMENT ANALYSIS METHOD BASED ON WEIBO COMMENTS

  • Li, Zhong-Shi;He, Lin;Guo, Wei-Jie;Jin, Zhe-Zhi
    • East Asian mathematical journal
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    • 제37권5호
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    • pp.599-612
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    • 2021
  • In China, Weibo is one of the social platforms with more users. It has the characteristics of fast information transmission and wide coverage. People can comment on a certain event on Weibo to express their emotions and attitudes. Judging the emotional tendency of users' comments is not only beneficial to the monitoring of the management department, but also has very high application value for rumor suppression, public opinion guidance, and marketing. This paper proposes a two-input Adaboost model based on TextCNN and BiLSTM. Use the TextCNN model that can perform local feature extraction and the BiLSTM model that can perform global feature extraction to process comment data in parallel. Finally, the classification results of the two models are fused through the improved Adaboost algorithm to improve the accuracy of text classification.

Plasminogen Activator Inhibitor-1 Antisense Oligodeoxynucleotides Abrogate Mesangial Fibronectin Accumulation

  • Park, Je-Hyun;Seo, Ji-Yeon;Ha, Hun-Joo
    • The Korean Journal of Physiology and Pharmacology
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    • 제14권6호
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    • pp.385-390
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    • 2010
  • Excessive extracellular matrix (ECM) accumulation is the main feature of chronic renal disease including diabetic nephropathy. Plasminogen activator inhibitor (PAI)-1 is known to play an important role in renal ECM accumulation in part through suppression of plasmin generation and matrix metalloproteinase (MMP) activation. The present study examined the effect of PAI-1 antisense oligodeoxynucleotide (ODN) on fibronectin upregulation and plasmin/MMP suppression in primary mesangial cells cultured under high glucose (HG) or transforming growth factor (TGF)-${\beta}1$, major mediators of diabetic renal ECM accumulation. Growth arrested and synchronized rat primary mesangial cells were transfected with $1\;{\mu}M$ phosphorothioate-modified antisense or control mis-match ODN for 24 hours with cationic liposome and then stimulated with 30 mM D-glucose or 2 ng/ml TGF-${\beta}1$. PAl-1 or fibronectin protein was measured by Western blot analysis. Plasmin activity was determined using a synthetic fluorometric plasmin substrate and MMP-2 activity analyzed using zymography. HG and TGF-${\beta}1$ significantly increased PAI-1 and fibronectin protein expression as well as decreased plasmin and MMP-2 activity. Transient transfection of mesangial cells with PAI-1 antisense ODN, but not mis-match ODN, effectively reversed basal as well as HG- and TGF-${\beta}1$-induced suppression of plasmin and MMP-2 activity. Both basal and upregulated fibronectin secretion were also inhibited by PAI-1 antisense ODN. These data confirm that PAI-1 plays an important role in ECM accumulation in diabetic mesangium through suppression of protease activity and suggest that PAI-1 antisense ODN would be an effective therapeutic strategy for prevention of renal fibrosis including diabetic nephropathy.

신호 대 잡음비 추정 방법을 이용한 다중 주파수 밴드 잡음 억제 시스템 (Multi frequency band noise suppression system using signal-to-noise ratio estimation)

  • 오인규;이인성
    • 한국음향학회지
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    • 제35권2호
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    • pp.102-109
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    • 2016
  • 본 논문은 밀접한 간격의 두 개의 마이크 배열 환경에서 SNR(Signal-to-Noise Ratio) 추정을 통한 잡음 억제 방법을 제안한다. 기존의 방법은 전 밴드에서 간섭 함수 기반의 SNR 추정을 통해 이득 함수를 얻는 잡음 억제 방법을 사용한다. 그러나 이 방법은 잡음으로 인한 손상이 모든 특징 벡터 성분에 영향을 미쳐 성능을 저하시키는 문제점을 가지고 있다. 따라서 주파수 영역의 신호를 N개의 다중 주파수 밴드로 구분하고 각 밴드별로 간섭 함수 기반의 SNR 추정을 통한 이득 함수를 얻는 잡음 억제 방법을 제안한다. 제안하는 방법의 성능평가는 ITU-T(International Telecommunications Union Telecommunication)에서 제공되는 객관적인 품질 평가 방법인 PESQ(Perceptual Evaluation of Speech Quality)로 비교하여 나타내었다.