• 제목/요약/키워드: Module Extraction

검색결과 211건 처리시간 0.035초

차량용 스택 고출력 내구성능 (High Durability of Stack for Automobile)

  • 김영민;이종현;윤종진;조장호
    • 한국신재생에너지학회:학술대회논문집
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    • 한국신재생에너지학회 2007년도 춘계학술대회
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    • pp.557-560
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    • 2007
  • The durability of 80 kW class stack module was tested in hydrogen recirculation and non-recirculation systems with the condition of 300Amps (constant current mode) and hydrogen pulse purging (10 seconds close/0.8 seconds open). A localized membrane failure in the interfacial area between membrane and sub-gasket, carbon corrosion in cathode electrode, and Pt dissolution/extraction have been found through the post mortem analysis such as CV, Impedance, SEM, and so on. The main reason of these mechanisms will be discussed in this study.

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Deep Reference-based Dynamic Scene Deblurring

  • Cunzhe Liu;Zhen Hua;Jinjiang Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권3호
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    • pp.653-669
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    • 2024
  • Dynamic scene deblurring is a complex computer vision problem owing to its difficulty to model mathematically. In this paper, we present a novel approach for image deblurring with the help of the sharp reference image, which utilizes the reference image for high-quality and high-frequency detail results. To better utilize the clear reference image, we develop an encoder-decoder network and two novel modules are designed to guide the network for better image restoration. The proposed Reference Extraction and Aggregation Module can effectively establish the correspondence between blurry image and reference image and explore the most relevant features for better blur removal and the proposed Spatial Feature Fusion Module enables the encoder to perceive blur information at different spatial scales. In the final, the multi-scale feature maps from the encoder and cascaded Reference Extraction and Aggregation Modules are integrated into the decoder for a global fusion and representation. Extensive quantitative and qualitative experimental results from the different benchmarks show the effectiveness of our proposed method.

MLSE-Net: Multi-level Semantic Enriched Network for Medical Image Segmentation

  • Di Gai;Heng Luo;Jing He;Pengxiang Su;Zheng Huang;Song Zhang;Zhijun Tu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권9호
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    • pp.2458-2482
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    • 2023
  • Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, MultiHead Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.

소수성 중공사 모듈에 의한 액-액 추출에 관한 연구 (A Study on the Liquid-Liquid Extraction by Use of Hydrophobic Hollow Fiber Module)

  • 김영일;박동원
    • 공업화학
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    • 제7권2호
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    • pp.237-244
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    • 1996
  • 미세공의 중공사 모듈을 이용한 액-액추출은 단위부피당 표면적이 크므로 기존 추출장치들에 비해 신속히 진행된다, 모듈내에서 추출제와 원료액은 빠른 속도로 접촉하며 두 흐름이 완전히 독립적이므로 부하나 편류현상이 일어나지 않는다. 본 연구에서는 소수성 중공사 모듈을 사용하여 수용액 중에 미량으로 존재하는 Fe(II)와 Ni(II)을 추출하기 위해 TOA 및 EHPNA를 추출제로 사용하여, 그 추출선택성을 고찰하였다. 또한, 중공사 모듈에서의 율속단계를 결정하기 위해 막 내 외부 유속의 영향을 검토하였다. 이로부터, 소수성 중공사 내에서 분배계수가 큰 계에 대한 추출조작의 경우는 막내부에서의 물질전달과정이 총괄물질전달을 지배함을 확인하였으며, 본 연구를 통한 $K_w$와 소수성 중공사 내부유속 $v_t$와의 상관관계는 $K_w{\frac{d}{D}}=6.22\(\frac{d^2v_t}{LD}\)^{1/3}$과 같았다. 반면, 분배계수가 낮은 경우, 세공 내에서의 추출반응이 원활하지 못하기 때문에 막내부 저항의 영향이 막저항의 영향보다 작았다. 따라서, 분배계수가 큰 계에서는 소수성 막을 사용하는 것이 효과적임을 예측할 수 있었다.

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문서 영상 내 테이블 영역에서의 단어 추출 (Word Extraction from Table Regions in Document Images)

  • 정창부;김수형
    • 정보처리학회논문지B
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    • 제12B권4호
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    • pp.369-378
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    • 2005
  • 문서 영상은 문서 구조 분석을 통하여 텍스트, 그림, 테이블 등의 세부 영역으로 분할 및 분류되는데, 테이블 영역에 있는 단어는 다른 영역의 단어보다 의미가 있기 때문에 주제어 검색과 같은 응용 분야에서 중요한 역할을 한다. 본 논문에서는 문서 영상의 테이블 영역에 존재하는 문자 성분을 단어단위로 추출하는 방법을 제안한다. 테이블 영역에서의 단어 추출은 실질적으로 테이블을 구성하는 셀 영역에서 단어를 추출하는 것이기 때문에 정확한 셀 추출 과정이 필요하다. 셀 추출은 연결 요소를 분석하여 테이블 프레임을 찾아내고, 교차점 검출은 전체가 아닌 테이블 프레임에 대해서만 수행한다. 잘못 검출된 교차점은 이웃하는 교차점과의 관계를 이용하여 수정하고, 최종 교차점 정보를 이용하여 셀을 추출한다. 추출된 셀 내부에 있는 텍스트 영역은 셀 추출 과정에서 분석한 문자성분의 연결 요소 정보를 재사용하여 결정하고, 결정된 텍스트 영역은 투영 프로파일을 분석하여 문자연로 분리된다. 마지막으로 분리된 문자열에 대하여 갭 군집화와 특수 기호 검출을 수행함으로써 단어 분리를 수행한다. 제안 방법의 성능 평가를 위하여 한글 논문 영상으로부터 추출한 총 In개의 테이블 영상에 대해 실험한 결과, $99.16\%$의 단어 추출 성공률을 얻을 수 있었다.

칼라 홍채영상을 이용한 홍채진단시스템 (An Iris Diagnosis System using Color Iris Images)

  • 한성현
    • 한국컴퓨터정보학회논문지
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    • 제13권6호
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    • pp.87-94
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    • 2008
  • 홍채진단은 홍채의 패턴, 색, 기타 다른 특징들을 조사하여 환자의 병을 진단하는 대체의학이다. 그러나 기존의 연구는 흑백 홍채영상을 이용하여 홍채 내의 특정 패턴을 검출하는 알고리즘 연구로 홍채의 칼라 정보로부터 건강상태를 체크하는 진단시스템으로 사용하기에는 부족하다. 본 논문에서는 칼라 홍채영상과 의료정보 데이터베이스를 이용하는 홍채진단시스템을 개발하였다. 개발한 시스템은 홍채카메라는 갖는 입력모듈, 홍채병소징후 검출 모듈, 의료정보 데이터베이스, 출력 모듈 등 4가지 모듈로 되어있다. 칼라 홍채영상으로부터 7가지 주요 홍채병소징후를 추출하고 검진의 정확도를 위해 병소 수동 편집 기능을 제공한다. 병소를 분석하는 단계에서는 홍채학에 기반한 의료정보와 개인 이력 관리 모듈을 이용한다. 제안한 시스템은 기존 시스템의 비해 다양한 기능이 추가되어 홍채진단 시스템으로 활용 가능하다.

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EDMFEN: Edge detection-based multi-scale feature enhancement Network for low-light image enhancement

  • Canlin Li;Shun Song;Pengcheng Gao;Wei Huang;Lihua Bi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권4호
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    • pp.980-997
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    • 2024
  • To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

An Operator Assisted Call Routing System

  • Lee, Chun-Jen;Jason S. Chang
    • 한국언어정보학회:학술대회논문집
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    • 한국언어정보학회 2002년도 Language, Information, and Computation Proceedings of The 16th Pacific Asia Conference
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    • pp.271-280
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    • 2002
  • A system to assist call routing task for telephone operators at the Directorate General of Telecommunications (DGT) in Taiwan is reported in this paper. The system was developed based on DGT organization profile with description of its six divisions instead of a corpus of recorded and transcribed call-routing dialogs. An acoustic module and an information retrieval module were built specifically for this task. The construction of IR module was based on term extraction and thesaurus discovery processes. By integrating acoustic and IR module, the system achieves satisfactory performance and provides a promising approach to call routing. Simulation results indicated that the proposed algorithm outperforms standard classification methods. A working system based on the proposed approach has been implemented and experimental results are presented.

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한국어 음성 분할을 위한 특징 검출에 관한 연구 (A Study on the Feature Extraction for the Segmentation of Korean Speech)

  • 이극;황희융
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1987년도 정기총회 및 창립40주년기념 학술대회 학회본부
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    • pp.338-340
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    • 1987
  • The speech recognition system usually consists of two modules, segmentation module and identification module. So, the performance of the system heavily depends on the segmentation accuracy and the segmentation unit. This paper is concerned with the agreeable features for segmentation in syllables. Total energy and two band width energy. (LE:4000-5000Hz and HE:900-3100Hz) are suitable cues for segmentation. And we testify it through the experiment using connected digit.

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원격작업 지시를 이용한 생물산업공정의 생력화 (I) -대상체 인식 및 3차원 좌표 추출- (Automation of Bio-Industrial Process Via Tele-Task Command(I) -identification and 3D coordinate extraction of object-)

  • 김시찬;최동엽;황헌
    • Journal of Biosystems Engineering
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    • 제26권1호
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    • pp.21-28
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    • 2001
  • Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.

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