• The Transactions of the Korea Information Processing Society
• /
• v.7 no.9
• /
• pp.2867-2875
• /
• 2000

In this paper, we discuss the implementation of automatic internet text categorization system. A categorization algorithm is designed and the system is implemented by back propagation learning model. Internet documents are collected according to the established categories and tested by Chi-squre ($\chi^2$) for the document leaning, and the category features are extracted. The sets of learning and separating vector are productt>d by these features. As a result of experimental evaluation, we show that this system is more improved in the performance of automatic categorization than the nearest neigbor method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.5 no.1
• /
• pp.33-44
• /
• 2012

A class of recurrent neural networks is proposed and proven to be capable of identifying any discrete-time dynamical system. The applications of the proposed network are addressed in the encoding, identification, and extraction of finite state automata. Simulation results show that the identification of finite state automata using the proposed network, trained by the hybrid greedy simulated annealing with a modified error function in the learning stage, exhibits generally better performance than other conventional identification schemes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.399-403
• /
• 2001

One of the most important factors for a leather quality inspection is its surface condition. So far, a leather quality level has been discriminated by human's eye inspection. But, these kinds of method needs a lot of labor time and cause decision mistakes from an optical illusion. It means leather quality inspection is very subjective and there is no consistency. In this study, we present computer vision based a leather quality inspection system using an Artificial intelligence. Suggested system can give standard spec for a leather quality and take human inspection duty place.

• Proceedings of the Korean Information Science Society Conference
• /
• 2000.04b
• /
• pp.21-23
• /
• 2000

공간 데이터베이스 시스템에서 객체간의 인접성을 유지해야하는 공간 객체의 갱신 연산 수행시, 이와 인접한 공간 객체들은 의미적 무결성을 상실하게 된다. 이러한 의미적 무결성을 만족하기 위해서는 수작업으로 무결성을 유지하는 수동적 무결성 유지 방법보다 사용자 편의성을 위해 자동 보정 연산의 지원이 필요하다. 본 논문에서는 공간 객체의 갱신 연산 수행시 인접한 공간 객체간의 의미적 무결성을 지원하기 위한 능동적인 공간 연산 트리거를 제안한다. 제안한 기법은 무결성 제약조건 검증 단계에서 인접한 공간 객체에 대한 자동 보정 연산을 수행하여 객체간의 의미적 무결성을 유지한다. 제안한 기법의 지원을 위해 무결성 제약조건은 레이어, 공간 객체의 순서로 기술하며, 무결성 검증 단계는 공간 객체, 레이어 순으로 제약조건 검사를 수행한다. 능동적 공간 연산 트리거는 레이어 제약조건 검증 단계에서 갱신연산에 대해 공간 위상 추출연산을 포함한 확장된 SQL을 사용하여 무결성을 유지하도록 한다. 능동적 공간 연산 트리거는 레이어 제약조건 검사와 공간 객체에 대한 자동 보정 연산의 수행을 통하여 인접성을 유지해야 하는 공간 객체들의 의미적 무결성과 사용자 편의성을 제공한다.

• Proceedings of the KSRS Conference
• /
• 2008.03a
• /
• pp.95-100
• /
• 2008

3차원으로 구성되어 있는 실세계를 보다 효과적이고 신속하게 모니터링하기 위해서는 변화된 지역의 정확한 위치정보 획득과 변화 결과의 빠른 도출을 위한 자동화 방안이 필요하다. 일반적으로 변화탐지를 위해 사용되어 온 항공사진이나 위성영상은 자료 획득에 있어 날씨와 같은 자연환경의 영향을 많이 받으며, 자동으로 변화탐지를 수행하는데 많은 문제점을 안고 있다. 반면에 항공 LiDAR 시스템은 영상시스템과는 달리 날씨 등에 영향을 상대적으로 적게 받으며, 지형지물에 대한 3차원 좌표 정보를 직접 획득하기 때문에 자동으로 처리하기에 매우 효율적이다. 본 연구에서는 항공 LiDAR 데이터만을 이용하여 도시지역의 시공간적 변화를 자동으로 탐지하는 방법을 연구 하였다. 변화탐지의 대상이 도시지역이므로 객체를 기반으로 다양한 변수를 사용하여 변화탐지를 수행하였다. 연구에 사용된 데이터는 서로 다른 시기에 획득된 항공 LiDAR 데이터이며, 두 데이터간의 변화탐지를 위해 먼저 상호정합을 수행하였으며, 개별 객체를 추출하기 위해 필터링과 Grouping 과정을 수행하였다. 마지막으로 Grouping된 객체를 대상으로 모양, 면적, 높이 변화를 비교하여 변화를 탐지하였다. 객체의 외곽선과 내부 영역의 모양을 표현하는 형상계수를 사용하므로 수평방향의 객체에 대한 기하학적인 모양 변화를 탐지할 수 있었으며, 객체의 높이값을 비교함으로써 수직방향으로의 변화도 탐지할 수 있었다. 본 연구에서 수행한 객체 기반의 변화탐지 방법은 91.67%의 전체 정확도를 획득하였다.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.2
• /
• pp.9-17
• /
• 2011

For the exact status of the land such as land cover classification and land use classification, feature classification system has been utilized in several organizations and agencies. However, those classification systems are limited to detection of land change and it's also not suited for the extraction of land changed. In this study, we would proposed a standard feature classification system which presents both in natural and artificial change of land effectively. Based on comparison and analysis of domestic and foreign relevant feature classification system, we proposed a standard feature classification system. In order to validate the applicability of the proposed feature classification system, we evaluated the accuracy with using automatic feature classification based on supervised classification and pre-knowledge hierarchical classification.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.5
• /
• pp.609-617
• /
• 2011

This paper proposes a personalized food recommendation system using user profiles auto-generated from Twitter. The user profiles are generated by extracting nouns from Twitter, and calculating emotional scores according to whether each noun is collocated with emotion words. Representative noun information for each food is constructed by analyzing web pages relevant to foods. Appropriate foods for users can be recommended by calculating similarities among the extracted resources. The proposed system has an advantage in that it can always recommend foods even if a user is a newcomer.

• The KIPS Transactions:PartB
• /
• v.11B no.5
• /
• pp.555-562
• /
• 2004

A genre or a style is another view of documents different from a subject or a topic. The style is also a criterion to classify the documents. There have been several studies on detecting a style of textual documents. However, only a few of them dealt with web documents. In this paper we suggest sets of features to detect styles of web documents. Web documents are different from textual documents in that Dey contain URL and HTML tags within the pages. We introduce the features specific to web documents, which are extracted from URL and HTML tags. Experimental results enable us to evaluate their characteristics and performances.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.10
• /
• pp.2409-2416
• /
• 2014

In this paper, an automatic recognition algorithm for linearly modulated signals like PSK, QAM under noncoherent asynchronous condition is proposed. Frequency, phase, and amplitude characteristics of digitally modulated signals are changed periodically. By using this characteristics, cyclic moments and higher order cumulants based features are utilized for the modulation recognition. Hierarchial decision tree method is used for high speed signal processing and totally 4 feature extraction parameters are used for modulation recognition. In the condition where the symbol number is 4,096, the recognition accuracy of the proposed algorithm is more than 95% at SNR 15dB. Also the proposed algorithm is effective to classify the signal which has carrier frequency and phase offset.

• Journal of KIISE:Software and Applications
• /
• v.31 no.6
• /
• pp.817-828
• /
• 2004

In this paper, we propose vector-based face generation system that uses montage and shading method and preserves designer(artist)'s style. Proposed system generates character's face similar to human face automatically using facial features that extracted from a photograph. In addition, unlike previous face generation system that uses contours, we propose the system is based on color and composes face from facial features and shade extracted from a photograph. Thus, it has advantages that can make more realistic face similar to human face. Since this system is vector-based, the generated character's face has no size limit and constraint. Therefore it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, it has distinctiveness with another approaches in point that can keep artist's impression just as it is in result.