• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.397-402
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• 2024

Speech recognition and motion recognition technologies are applied and used in various smart devices, but they are composed of simple command recognition forms and are used as simple functions. Apart from simple functions for recognition data, professional command execution capabilities are required based on data learned in various fields. Research is being conducted on a system platform that provides optimal data to users using Generative AI, which is currently competing around the world, and can interact through voice recognition and motion recognition. The main technical processes designed for this study were designed using technologies such as voice and motion recognition functions, application of AI technology, and two-way communication. In this paper, two-way communication between a device and a user can be achieved by various input methods through voice recognition and motion recognition technology applied with AI technology.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.164-170
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• 2008

This research was verified detection way of intercept vehicles and performance evaluation after system installation using image detector as detection way of ground installation. By image recognition algorithm was on the trace of moving orbit of violation vehicles for detection way of intercept vehicles. When moving orbit is located special site, utilized geometric image calibration and DC-notch filter. These are cognitive system of license plate by making signal. Then, Bright Evidence Detection and Dark Evidence Detection were applied to after mixing. It is applied to way of Backward tracking for detection way of intercept vehicles. After the field evaluation of developed system, it should be analyzed the more high than recognition rate of minimum standards 80%. It should rise in the estimation of the site applicability is highly from now.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.172-174
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• 2004

This paper proposes an integerized approach to solve PCA(Principal Component Analysis) feature extract procedure mainly used for the face recognition. A simple conversion to integer values has the risk to reduce the precision compared to that of the floating points operations. We integerize the PC variables by normalizing with the maximum of them, and show the efficiency of the proposed scheme by comparing the results to those of the float/double precisions. The integerized scheme is expected to be an efficient way for the real-time implementation of PCA's recognition stage, because integer operator is more desirable than floating point ones. Further research is to find a way to implement face detection and to measure the distances from the stored PCs for the full real-time face recognition.

• Journal of Korean Library and Information Science Society
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• v.34 no.2
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• pp.19-42
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• 2003

The purpose of this study is to identify the way of development of school library and construction of information system for school library. In order to identify the way, the school librarian recognition level of school library information system was analyzed, since the recognition level about the information system can affect the school library development. Data is collected through the questionnaire. The result can be used to develope a school library instruction program for teachers and a base material for recovering the school library fundamental function.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.10-17
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• 2017

This study is the first attempt to raise face recognition ability through machine learning algorithm and apply to CRM's information gathering, analysis and application. In other words, through face recognition of VIP customer in distribution field, we can proceed more prompt and subdivided customized services. The interest in machine learning, which is used to implement artificial intelligence, has increased, and it has become an age to automate it by using machine learning beyond the way that a person directly models an object recognition process. Among them, Deep Learning is evaluated as an advanced technology that shows amazing performance in various fields, and is applied to various fields of image recognition. Face recognition, which is widely used in real life, has been developed to recognize criminals' faces and catch criminals. In this study, two image analysis models, TF-SLIM and Inception-V3, which are likely to be used for criminal face recognition, were selected, analyzed, and implemented. As an evaluation criterion, the image recognition model was evaluated based on the accuracy of the face recognition program which is already being commercialized. In this experiment, it was evaluated that the recognition accuracy was good when the accuracy of the image classification was more than 90%. A limit of our study which is a way to raise face recognition is left as a further research subjects.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.715-719
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• 1991

In manufacturing process, usually 2-dimensional part drawing is used as a basic data. If a designer wants to recognize 2-dimensional drawing and formulate 3-dimensional shape, a proper feature recognition rule is required as a prerequisite step. These rules are converted Into knowledge base, should be ed separately in the recognition program and can be referenced In similar way of database application. In this paper, basic feature recognition rules are addressed in structure type knowledge base, and the application system is formulated which can be operated separately with existing data driven program.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.481-483
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• 1989

This paper is concentrated on the recognition of Korean Digits. The speech signals of each of digits are fed into computer through the 18 bandpass filters, AD converter. Spectrum input data are analyzed and used. BASIC program language is used for recognition performance and the result of recognition is outputed to computer screen and printer. In this paper, the strength and weakness of filter-bank analysis method is described and the technique of real-time recognition is argued. In this experiment, Ratio of recognition for speaker dependent recognition was about 97% and recognition time was also satisfied. Therefore, A way of speaker independent recognition will be presented and using for special communication in the future.

• Journal of Korea Game Society
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• v.12 no.1
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• pp.123-132
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• 2012

There are many of games using smart devices. Voice recognition is can be useful way for input. In the game, voice have to be quickly recognized, at the same time it have to be manipulated promptly as well. In this study, we developed the optimized real-time phoneme recognition using max flow matching that it can be efficiently used in the game field. Firstly, voice wavelength is transformed to FFT, secondly, transformed value is made by a graph in Z plane, thirdly, data is extracted in specific area, and then data is saved in database. After all the value is recognized using weighted bipartite max flow matching. This way would be useful method in game or robot field when researchers hope to recognize the fast voice recognition.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.128-136
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• 2013

Recently, the localization recognition system research has been studied using various sensors according to increased interest in autonomous navigation flight. In case of indoor environment which cannot support GPS information, we have to look for another way to recognize current position. The Image-based localization recognition system has been interested although there are lots of way to know current pose. In this paper, we explain the localization recognition system based on mark and implementation of autonomous navigation flight. In order to apply to real environment which cannot support marks, localization based on real-time 3D map building is discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.141-146
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• 2014

This paper describes the implementation and algorithm of handwritten character recognition using mobile touch screen. The system is consisted of PXA320 processor, capacitive touch panel and QT4 interface. The proposed algorithm extracts pattern characteristics with straight, left circle, right circle on the inputting character. The definition of character is determined by 3-way tree searching method. The performance of proposed algorithm is verified using alphabet character. It is suitable to apply the mobile touch screen because of simple algorithm.