• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.7
• /
• pp.641-648
• /
• 2001

A face detection in color images is important for many multimedia applications. It is first step for face recognition and can be used for classifying specific shorts. This paper describes a new method to detect faces in color images based on the skin color and hair color. This paper presents a fuzzy-based method for classifying skin color region in a complex background under varying illumination. The Fuzzy rule bases of the fuzzy system are generated using training method like a genetic algorithm(GA). We find the skin color region and hair color region using the fuzzy system and apply the convex-hull to each region and find the face from their intersection relationship. To validity the effectiveness of the proposed method, we make experiment with various cases.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10b
• /
• pp.929-932
• /
• 1990

This paper considers the problem of patterns recognition using the artificial neural network systems. The artificial neural network systems provide an effective tool for classifying patterns and/or characters by learning them in a certain repeated hashion. The mechanism of the learning process and the structure of neural network systems used are main concerns in the accurate and fast classification of the patterns which are slightly different each other. The neural network system employed in this study has three layers structure which is composed of input, intermidiate, and output layers. Our main concern is to develope an effective learning mechanism how to learn the patterns fastly and accurately. The experimental study performed shows that there exists an effective learning method to get higher recognition ratio in classifying the several different patterns by artificial neural network system constructed.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.473-477
• /
• 2001

Artificial neural network (ANN) is known to identify relationships even when some of the input data are very complex, ill-defined and ill-structured. One of the advantages in ANN is that it can discriminate the linearly inseparable data. This study presents an application of ANN to classify and predict the symptomatic status of HIV/AIDS patients. Even though ANN techniques have been applied to a variety of areas, this study has a substantial contribution to the HIV/AIDS care and prevention planning area. ANN model in classifying both the HIV and AIDS status of HIV/AIDS patients is developed and analyzed. The diagnostic accuracy of the ANN in classifying both the HIV status and AIDS status of HIV/AIDS status is evaluated. Several different ANN topologies are applied to AIDS Cost and Services Utilization Survey (ACSUS) datasets in order to demonstrate the model\`s capability. If ANN design models are different, it would be interesting to see what influence would have on classification of HIV/AIDS-related persons.

• Spatial Information Research
• /
• v.10 no.3
• /
• pp.385-406
• /
• 2002

The purpose of this paper is to search for the construction of UDS(Urban Diagnosis System) which can be effectively applied to selecting or classifying the districts for carving out projects of urban planning based on urban geographic information. In order to promote projects of urban planning, it is essential that selecting or classifying the urban districts should be precisely diagnosed according to the respective blocks. Objective measuring standards are needed for this, and the UDS can be applied to analyzing these standards according to the levels. With these in mind, this paper will consider the present states of Korea and the established states of developed countries. Besides, the interest of this paper is to seek the ways of utilizing GIS most effectively in the urban planning areas and application methods. Also, it will find the ways of applying UDS extensively to selecting or classifying districts far the purpose of carrying out urban planning projects actually in the case areas.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.5 no.1
• /
• pp.34-47
• /
• 1985

The developing country, KOREA where does not possess the natural resources for traditional energy such as oil and gas, so. The nuclear energy is the most single reliable source available for closing the energy gap. For these reason, It is inavoidable to construct the nuclear power plant and to develop technology related nuclear energy. The rate of operation in large nuclear power facilities depends upon the performance of work system through design and construction, and also the applied technology. Especially, it is the most important element that safety and reliability in operation of nuclear power plant. In view of this aspects, Nuclear power plant is performed severe examinations during preservice and inservice inspection. This study provide an automation of analysis for volumetric examination which is required to nuclear power plant components. It is composed as follows: I. Introduction II. Inservice Inspection of Nuclear Power Plant ${\ast}$ General Requirement. ${\ast}$ Principle and Methods of Ultrasonic Test. ${\ast}$ Study of Flaw Evaluation and Design of Classifying Formula for Flaws. III. Design of Automation for Flaw Evaluation. IV. An Example V. Conclusion In this theory, It is classifying the flaws, the formula of classifying flaws and the design of automation that is the main important point. As motioned the above, Owing to such as automatic design, more time could be allocated to practical test than that of evaluation of defects, Protecting against subjective bias tester by himself and miscalculation by dint of various process of computation. For the more, adopting this method would be used to more retaining for many test data and comparative evaluating during successive inspection intervals. Inspite of limitation for testing method and required application to test components, it provide useful application to flow evaluation for volumetric examination. Owing to the characteristics of nuclear power plant that is highly skill intensive industry and has huze system, the more notice should be concentrated as follows. Establishing rational operation plan, developing various technology, and making the newly designed system for undeveloped sector.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.2
• /
• pp.331-336
• /
• 2017

The need for early fire detection technology is increasing in order to prevent fire disasters. Sensor device detection for heat, smoke and fire is widely used to detect flame and smoke, but this system is limited by the factors of the sensor environment. To solve these problems, many image-based fire detection systems are being developed. In this paper, we implemented a system to detect fire and smoke from camera input images using a convolution neural network. Through the implemented system using the convolution neural network, a feature map is generated for the smoke image and the fire image, and learning for classifying the smoke and fire is performed on the generated feature map. Experimental results on various images show excellent effects for classifying smoke and fire.

• Journal of the Korean Home Economics Association
• /
• v.38 no.10
• /
• pp.45-51
• /
• 2000

This study illucidated the importance of drop Value in the resets of surveying the current values of sizing and grading. Therefore, it is meaningful to get the classification of body form with the appropriate distribution of drop values of the body. The distribution of drop value and the frequency of each form is very helpful to name the combined sizing or coverage of ready-made clothes. This study aimed at classifying body forms with various drop values using multivariate analysis for sizing and grading. Factor analysis and cluster analysis were done using measured values from unmarried women. The resets are as follows; The factor which explains body forms was obtained by factor analysis, and the representative major 18 items which have important roles in classifying body forms were selected among the measured values with high factor loading and communality. 1) The body forms were classified into 3 groups based on the characteristics, frequencies and distributions of them obtained from cluster analysis. 2) Each classified body form showed conspicuous difference in drop value and the difference of body form mainly resulted from the difference between bust and hip(drop value) in Korean unmarried women. 3) Discriminant analysis showed that the most significant discriminant factor of the trunk classification were bust circumference, upper bust circumference, hip circumference and stature. 4) The cover ratio of size studied in this study for the Korean Sizing system for women's garment were founded high.

• The Journal of Korean Philosophical History
• /
• no.54
• /
• pp.115-151
• /
• 2017

With Seopa Ryu-Hee's Chunqiugwalyebulyu as the main research subject. this paper is to clarify characteristics in classification of the book's introductory remarks and its academic values. This book is a sort of synthetic collection of introductory remarks classification that defines standardized introductory remarks based on fundamental principles of Chunqiu introductory remarks. Seopa presented two fundamental principles for classifying Chunqiu introductory remarks. First, he clearly defined the nature and the system of the book Chunqiu, which was to present the background of classifying Chunqiu introductory remarks. Second, he declared that writing style and righteousness in Chunqiu serves as standard for classifying the introductory remarks. Seopa classified introductory remarks by type in accordance with these fundamental principles of introductory remarks in order to lay the groundwork for right interpretation of Chunqiu. Further, he was convinced that this classification of introductory remarks would block any chance of the book's wrong interpretation and at the same time, be able to remove the rationale behind distorted theories. This book can be appraised to have significant academic values in that it attempted standardization in classifying Chunqiu introductory remarks through systematic and synthetic analysis on various introductory remarks.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.126-128
• /
• 2004

As e-mail is becoming increasingly important in every day life activity, mail users spend more and more time organizing and classifying the e-mails they receive into folder. Many existing recommendation systems or text classification are mostly focused on recommending the products for the commercial purposes or web documents. So this study aims to apply these application to e-mail more necessary to users. This paper suggests a dynamic recommendation agent system based on Rule Filtering Component recommending the relevant category to enable users directly to manage the optimum classification when a new e-mail is received as the effective method for E-Mail Management. Moreover we try to improve the accuracy as eliminating the limits of misclassification that can be key in classifying e-mails by category. While the existing Bayesian Learning Algorithm mostly uses the fixed threshold, we prove to improve the satisfaction of users as increasing the accuracy by changing the fixed threshold to the dynamic threshold. We designed main modules by rule filtering component for enhanced scalability and reusability of our system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.3
• /
• pp.256-261
• /
• 2013

In the steel manufacturing area, researches for defect inspection receive a big attention for quality control. This paper proposes an algorithm to detect a scratch defect on steel billets. This algorithm takes ROIs (Regions of Interest), and extracts 11 features which represent properties of defect on a ROI. SVM (Support Vector Machine) is used to classify defect and normal ROIs. The algorithm classifies a frame image of a Billet as a defect image if there is one or more defect ROIs. In the experiments, the proposed algorithm had reliable classifying accuracy.