• 제목/요약/키워드: Automatic Recognition System

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Developing an Automatic Classification System Based on Colon Classification: with Special Reference to the Books housed in Medical and Agricultural Libraries (콜론분류법에 바탕한 자동분류시스템의 개발에 관한 연구 - 농학 및 의학 전문도서관을 사레로 -)

  • Lee Kyung-Ho
    • Journal of the Korean Society for Library and Information Science
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    • v.23
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    • pp.207-261
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    • 1992
  • The purpose of this study is (1) to design and test a database which can be automatically classified, and (2) to generate automatic classification number by processing the keywords in titles using the code combination method of Colon Classification(CC) as well as an automatic recognition of subjects in order to develop an automatic classification system (Auto BC System) based on CC which can be applied to any research library. To conduct this study, 1,510 words in the fields of agricultrue and medicine were selected, analized in terms of [P], [M], [E], [S], [T] employed in CC, and included in a database for classification. For the above-mentioned subject fields, the principle of an automatic classification was specified in order to generate automatic classification codes as well as to perform an automatic subject recognition of the titles included. Whenever necessary, editing, deleting, appending and reindexing of a database can be made in this automatic classification system. Appendix 1 shows the result of the automatic classification of books in the fields of agriculture and medicine. The results of the study are summarized below. 1. The classification number for the title of a book can be automatically generated by using the facet principles of Colon Classification. 2. The automatic subject recognition of a book is achieved by designing a database making use of a globe-principle, and by specifying the subject field for each word. 3. The automatic subject-recognition of input data is achieved by measuring the number of searched words by each subject field. 4. The combination of classification numbers is achieved by flowcharting of classification formular of each subject field. 5. The efficient control of classification numbers is achieved by designing control codes on the database for classification. 6. The automatic classification by means of Auto BC has been proved to be successful in the research library concentrating on a Single field. The general library may have some problem in employing this system. The automatic classification through Auto BC has the following advantages: 1. Speed of the classification process can be improve. 2. The revision or updating of classification schemes can be facilitated. 3. Multiple concepts can be expressed in a single classification code. 4. The consistency of classification can be achieved with the classification formular rather than the classifier's subjective judgement. 5. A user's retrieving process can be made after combining the classification numbers through keywords relating to the material to be searched. 6. The materials can be classified by a librarian without subject backgrounds. 7. The large body of materials can be quickly classified by means of a machine processing. 8. This automatic classification is expected to make a good contribution to design of the total system for library operations. 9. The information flow among libraries can be promoted owing to the use of the same program for the automatic classification.

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Building an Exceptional Pronunciation Dictionary For Korean Automatic Pronunciation Generator (한국어 자동 발음열 생성을 위한 예외발음사전 구축)

  • Kim, Sun-Hee
    • Speech Sciences
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    • v.10 no.4
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    • pp.167-177
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    • 2003
  • This paper presents a method of building an exceptional pronunciation dictionary for Korean automatic pronunciation generator. An automatic pronunciation generator is an essential element of speech recognition system and a TTS (Text-To-Speech) system. It is composed of a part of regular rules and an exceptional pronunciation dictionary. The exceptional pronunciation dictionary is created by extracting the words which have exceptional pronunciations from text corpus based on the characteristics of the words of exceptional pronunciation through phonological research and text analysis. Thus, the method contributes to improve performance of Korean automatic pronunciation generator as well as the performance of speech recognition system and TTS system.

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HMM-Based Automatic Speech Recognition using EMG Signal

  • Lee Ki-Seung
    • Journal of Biomedical Engineering Research
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    • v.27 no.3
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    • pp.101-109
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    • 2006
  • It has been known that there is strong relationship between human voices and the movements of the articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The EMG signals were acquired from three articulatory facial muscles. Preliminary, 10 Korean digits were used as recognition variables. The various feature parameters including filter bank outputs, linear predictive coefficients and cepstrum coefficients were evaluated to find the appropriate parameters for EMG-based speech recognition. The sequence of the EMG signals for each word is modelled by a hidden Markov model (HMM) framework. A continuous word recognition approach was investigated in this work. Hence, the model for each word is obtained by concatenating the subword models and the embedded re-estimation techniques were employed in the training stage. The findings indicate that such a system may have a capacity to recognize speech signals with an accuracy of up to 90%, in case when mel-filter bank output was used as the feature parameters for recognition.

CAD/CAPP System based on Manufacturing Feature Recognition (제조특징인식에 의한 CAD/CAPP 시스템)

  • Cho, Kyu-Kab;Kim, Suk-Jae
    • Journal of the Korean Society for Precision Engineering
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    • v.8 no.1
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    • pp.105-115
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    • 1991
  • This paper describes an integrated CAD and CAPP system for prismatic parts of injection mold which generates a complete process plan automatically from CAD data of a part without human intervention. This system employs Auto CAD as a CAD model and GS-CAPP as an automatic process planning system for injection mold. The proposed CAD/CAPP system consists of three modules such as CAD data conversion module, manufacturing feature recognition module, and CAD/CAPP interface module. CAD data conversion module transforms design data of AutoCAD into three dimensional part data. Manufacturing feature recognition module extracts specific manufacturing features of a part using feature recognition rule base. Each feature can be recognized by combining geometry, position and size of the feature. CAD/CAPP interface module links manufacturing feature codes and other head data to automatic process planning system. The CAD/CAPP system can improve the efficiency of process planning activities and reduce the time required for process planning. This system can provide a basis for the development of part feature based design by analyzing manufacturing features.

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The Road Traffic Sign Recognition and Automatic Positioning for Road Facility Management (도로시설물 관리를 위한 교통안전표지 인식 및 자동위치 취득 방법 연구)

  • Lee, Jun Seok;Yun, Duk Geun
    • International Journal of Highway Engineering
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    • v.15 no.1
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    • pp.155-161
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    • 2013
  • PURPOSES: This study is to develop a road traffic sign recognition and automatic positioning for road facility management. METHODS: In this study, we installed the GPS, IMU, DMI, camera, laser sensor on the van and surveyed the car position, fore-sight image, point cloud of traffic signs. To insert automatic position of traffic sign, the automatic traffic sign recognition S/W developed and it can log the traffic sign type and approximate position, this study suggests a methodology to transform the laser point-cloud to the map coordinate system with the 3D axis rotation algorithm. RESULTS: Result show that on a clear day, traffic sign recognition ratio is 92.98%, and on cloudy day recognition ratio is 80.58%. To insert exact traffic sign position. This study examined the point difference with the road surveying results. The result RMSE is 0.227m and average is 1.51m which is the GPS positioning error. Including these error we can insert the traffic sign position within 1.51m CONCLUSIONS: As a result of this study, we can automatically survey the traffic sign type, position data of the traffic sign position error and analysis the road safety, speed limit consistency, which can be used in traffic sign DB.

Rule-based Named Entity (NE) Recognition from Speech (음성 자료에 대한 규칙 기반 Named Entity 인식)

  • Kim Ji-Hwan
    • MALSORI
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    • no.58
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    • pp.45-66
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    • 2006
  • In this paper, a rule-based (transformation-based) NE recognition system is proposed. This system uses Brill's rule inference approach. The performance of the rule-based system and IdentiFinder, one of most successful stochastic systems, are compared. In the baseline case (no punctuation and no capitalisation), both systems show almost equal performance. They also have similar performance in the case of additional information such as punctuation, capitalisation and name lists. The performances of both systems degrade linearly with the number of speech recognition errors, and their rates of degradation are almost equal. These results show that automatic rule inference is a viable alternative to the HMM-based approach to NE recognition, but it retains the advantages of a rule-based approach.

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Smart Phone Road Signs Recognition Model Using Image Segmentation Algorithm

  • Huang, Ying;Song, Jeong-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.887-890
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    • 2012
  • Image recognition is one of the most important research directions of pattern recognition. Image based road automatic identification technology is widely used in current society, the intelligence has become the trend of the times. This paper studied the image segmentation algorithm theory and its application in road signs recognition system. With the help of image processing technique, respectively, on road signs automatic recognition algorithm of three main parts, namely, image segmentation, character segmentation, image and character recognition, made a systematic study and algorithm. The experimental results show that: the image segmentation algorithm to establish road signs recognition model, can make effective use of smart phone system and application.

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Detection of Stator Winding Inter-Turn Short Circuit Faults in Permanent Magnet Synchronous Motors and Automatic Classification of Fault Severity via a Pattern Recognition System

  • CIRA, Ferhat;ARKAN, Muslum;GUMUS, Bilal
    • Journal of Electrical Engineering and Technology
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    • v.11 no.2
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    • pp.416-424
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    • 2016
  • In this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.

Automatic Defects Recognition System for Visual Inspection on Concrete Tunnel Lining (콘크리트 터널 라이닝의 외관조사를 위한 자동화 결함인식 시스템 개발)

  • Park, Seok-Kyun;Lee, Kang-Moon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6A
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    • pp.873-880
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    • 2008
  • When checking the state of deterioration or damage structures, regular visual inspection has very important role. At this point, a visual inspection is performed mainly by sketch or photography with a camera of inspectors. If that happens, it takes a lot of effort and time to inspect appearance damages. The purpose of this study is to develop the automatic recognition system for a more efficient and effective inspection of appearance damages. In the process, the image processing technology and the data management & analysis system for damage recognition are mainly developed and applied. This automatic recognition system enables inspectors or clients to obtain correct data that can recognize a damage, such as, crack, water leakage, efflorescence, delamination (peeling), spalling, etc. In addition, this study takes aim at the effect of secure safety, functional maintenance and extension of design lifetime according to build up continuous and systematic data management system.

Automatic conversion of machining data by the recognition of press mold (프레스 금형의 특징형상 인식에 의한 가공데이터 자동변환)

  • 최홍태;반갑수;이석희
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1994.04a
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    • pp.703-712
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    • 1994
  • This paper presents an automatic conversion of machining data from the orthographic views of press mold by feature recognition rule. The system includes following 6 modules : separation of views, function support, dimension text recognition, feature recognition, dimension text check and feature processing modules. The characteristic of this system is that with minimum user intervention, it recognizes basic features such as holes, slots, pockets and clamping parts and thus automatically converts CAD drawing details of press mold into machining data using 2D CAD system instead of using an expensive 3D Modeler. The system is developed by using IBM-PC in the environment of AutoCAD R12, AutoLISP and MetaWare High C. Performance of the system is verified as a good interfacing of CAD and CAM when applied to a lot of sample drawings.