• Title/Summary/Keyword: Automatic convert

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SuperDepthTransfer: Depth Extraction from Image Using Instance-Based Learning with Superpixels

  • Zhu, Yuesheng;Jiang, Yifeng;Huang, Zhuandi;Luo, Guibo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4968-4986
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    • 2017
  • In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

The Region Analysis of Document Images Based on One Dimensional Median Filter (1차원 메디안 필터 기반 문서영상 영역해석)

  • 박승호;장대근;황찬식
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.3
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    • pp.194-202
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    • 2003
  • To convert printed images into electronic ones automatically, it requires region analysis of document images and character recognition. In these, regional analysis segments document image into detailed regions and classifies thee regions into the types of text, picture, table and so on. But it is difficult to classify the text and the picture exactly, because the size, density and complexity of pixel distribution of some of these are similar. Thu, misclassification in region analysis is the main reason that makes automatic conversion difficult. In this paper, we propose region analysis method that segments document image into text and picture regions. The proposed method solves the referred problems using one dimensional median filter based method in text and picture classification. And the misclassification problems of boldface texts and picture regions like graphs or tables, caused by using median filtering, are solved by using of skin peeling filter and maximal text length. The performance, therefore, is better than previous methods containing commercial softwares.

Noise-Robust Porcine Respiratory Diseases Classification Using Texture Analysis and CNN (질감 분석과 CNN을 이용한 잡음에 강인한 돼지 호흡기 질병 식별)

  • Choi, Yongju;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.3
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    • pp.91-98
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    • 2018
  • Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. In particular, porcine respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this paper, we propose a noise-robust system for the early detection and recognition of pig wasting diseases using sound data. In this method, first we convert one-dimensional sound signals to two-dimensional gray-level images by normalization, and extract texture images by means of dominant neighborhood structure technique. Lastly, the texture features are then used as inputs of convolutional neural networks as an early anomaly detector and a respiratory disease classifier. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (low-cost sound sensor) and accurately (over 96% accuracy) even under noise-environmental conditions, either as a standalone solution or to complement known methods to obtain a more accurate solution.

Automatic Generation of Web-based Expert Systems (웹 기반 전문가시스템의 자동생성체계)

  • 송용욱
    • Journal of Intelligence and Information Systems
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    • v.6 no.1
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    • pp.1-16
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    • 2000
  • This paper analyzes the approaches of Web-based expert systems by comparing their pros and cons. and proposes a methodology of implementing the Web-based backward inference engines with reduced burden to Web servers. There are several alternatives to implement expert systems under the WWW environment : CGI, Web servers embedding inference engines external viewers Java Applets and HTML. Each of the alternatives have advantages and disadvantages of each own in terms of development and deployment testing scalability portability maintenance and mass service. Especially inference engines implemented using HTML possess relatively large number of advantages compared with those implemented using other techniques. This paper explains the methodology to present rules and variables for backward inference by HTML and JavaScript and suggests a framework for design and development of HTML-based Expert System. A methodology to convert a traditional rule base to an Experts Diagram and then generate a new HTML-based Expert System from the Experts Diagram is also addressed.

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Aspect Mining Process Design Using Abstract Syntax Tree (추상구문트리를 이용한 어스팩트 마이닝 프로세스 설계)

  • Lee, Seung-Hyung;Song, Young-Jae
    • The Journal of the Korea Contents Association
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    • v.11 no.5
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    • pp.75-83
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    • 2011
  • Aspect-oriented programming is the paradigm which extracts crosscutting concern from a system and solves scattering of a function and confusion of a code through software modularization. Existing aspect developing method has a difficult to extract a target area, so it is not easy to apply aspect mining. In an aspect minning, it is necessary a technique that convert existing program refactoring elements to crosscutting area. In the paper, it is suggested an aspect mining technique for extracting crosscutting concern in a system. Using abstract syntax structure specification, extract functional duplicated relation elements. Through Apriori algorithm, it is possible to create a duplicated syntax tree and automatic creation and optimization of a duplicated source module, target of crosscutting area. As a result of applying module of Berkeley Yacc(berbose.c) to mining process, it is confirmed that the length and volume of program has been decreased of 9.47% compared with original module, and it has been decreased of 4.92% in length and 5.11% in volume compared with CCFinder.

Design and Implementation of a Paper Submission Management System Using Domain Object Interface and Object Oriented Design Patterns (객체지향 설계 유형 및 도메인 객체 인터페이스를 이용한 논문 투고 관리 시스템 설계 및 구현)

  • Sim, Chun-Bo;Jung, Se-Hoon;Lim, Eun-Cheon;You, Kang-Soo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.5
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    • pp.449-458
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    • 2010
  • Recently, the interest on object oriented design patterns has been increased considering to reusability of software and efficiency of maintenance expense in designing software architecture. In this paper, we design the paper submission management system applicable to specific domain using domain object interface based on object oriented design patterns, and then implement it with Java and XML. The proposed system applies method of implementation by assemblying each system objects with upward after system entire architecture design by combining properly downward method and upward method and applies with GoF Design pattern. As well as, we convert domain data of system into the form of various persistent objects through XML, and minimize the complexity of system by not adopting method that generates domain object as in Class with automatic. Finally, the implementation of our system can be used in general C/S environment, but we implement system user GUI using the XSLT built in general web browser in consideration for user convenience and consistency.

Rainfall Estimation by X-band Marine Radar (X밴드 선박용 레이더를 이용한 강우 추정)

  • Kim, Kwang-Ho;Kwon, Byung-Hyuk;Kim, Min-Seong;Kim, Park-Sa;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.4
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    • pp.695-704
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    • 2018
  • The rainfall cases were identified by rainfall estimation techniques which were developed by using X - band marine radar. A digital signal converter was used to convert the signal received from the marine radar into digital reflectivity information. The ground clutter signal was removed and the errors caused by beam attenuation and beam volume changes were corrected. The reflectivity showed a linear relationship with the rain gauge rainfall. Quantitative rainfall was estimated by converting the radar signal into an cartesian coordinate system. When the rainfall was recorded more than $5mm\;hr^{-1}$ at three automatic weather stations, the rain cell distribution on the marine radar was consistent with that of the weather radar operated by Korea meteorological Adminstration.

Automatic Conversion of English Pronunciation Using Sequence-to-Sequence Model (Sequence-to-Sequence Model을 이용한 영어 발음 기호 자동 변환)

  • Lee, Kong Joo;Choi, Yong Seok
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.5
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    • pp.267-278
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    • 2017
  • As the same letter can be pronounced differently depending on word contexts, one should refer to a lexicon in order to pronounce a word correctly. Phonetic alphabets that lexicons adopt as well as pronunciations that lexicons describe for the same word can be different from lexicon to lexicon. In this paper, we use a sequence-to-sequence model that is widely used in deep learning research area in order to convert automatically from one pronunciation to another. The 12 seq2seq models are implemented based on pronunciation training data collected from 4 different lexicons. The exact accuracy of the models ranges from 74.5% to 89.6%. The aim of this study is the following two things. One is to comprehend a property of phonetic alphabets and pronunciations used in various lexicons. The other is to understand characteristics of seq2seq models by analyzing an error.

DEVELOPMENT AND IMPLEMENTATION OF DISTRIBUTED HARDWARE-IN-THE-LOOP SIMULATOR FOR AUTOMOTIVE ENGINE CONTROL SYSTEMS

  • YOON M.;LEE W.;SUNWOO M.
    • International Journal of Automotive Technology
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    • v.6 no.2
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    • pp.107-117
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    • 2005
  • A distributed hardware-in-the-loop simulation (HILS) platform is developed for designing an automotive engine control system. The HILS equipment consists of a widely used PC and commercial-off-the-shelf (COTS) I/O boards instead of a powerful computing system and custom-made I/O boards. The distributed structure of the HILS system supplements the lack of computing power. These features make the HILS equipment more cost-effective and flexible. The HILS uses an automatic code generation extension, REAL-TIME WORKSHOP$^{ (RTW$^{) of MATLAB$^{ tool-chain and RT-LAB$^{, which enables distributed simulation as well as the detection and generation of digital event between simulation time steps. The mean value engine model, which is used in control design phase, is imported into this HILS. The engine model is supplemented with some I/O subsystems and I/O boards to interface actual input and output signals in real-time. The I/O subsystems are designed to imitate real sensor signals with high fidelity as well as to convert the raw data of the I/O boards to the appropriate forms for proper interfaces. A lot of attention is paid to the generation of a precise crank/ earn signal which has the problem of quantization in a conventional fixed time step simulation. The detection of injection! command signal which occurs between simulation time steps are also successfully compensated. In order to prove the feasibility of the proposed environment, a simple PI controller for an air-to-fuel ratio (AFR) control is used. The proposed HILS environment and I/O systems are shown to be an efficient tool to develop various control functions and to validate the software and hardware of the engine control system.

A method for automatic EPC code conversion based on ontology methodology (온톨로지 기반 EPC 코드 자동 변환 방법)

  • Noh, Young-Sik;Byun, Yung-Cheol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.3
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    • pp.452-460
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    • 2008
  • ALE-complient RFID middleware system receives EPC code data from reader devices and converts the data into URN format data internally. After filtering and grouping, the system sends the resulting URN code to application and(or) users. Meanwhile, not only the types of EPC code are very diverse, but also another new kinds of EPC code can be emerged in the future. Therefore, a method to process all kinds of EPC code effectively is required by RFID middleware. In this paper, a method to process various kinds of EPC code acquired from RFID reader devices in ALE-complient RFID middleware is proposed. Especially, we propose an approach using ontology technology to process not only existing EPC code but also newly defined code in the future. That is, we build an ontology of conversion rules for each EPC data type to effectively convert EPC data into URL format data. In this case, we can easily extend RFID middleware to process a new EPC code data by adding a conversion rule ontology for the code.