• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.190-194
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. Because high-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system with iris feature extraction methods based on USN(Ubiquitous Sensor Network). Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.419-428
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• 2020

SNS media is gaining its media share with the benefits of digital technology, such as the convenience of physical access and the entertainment and interactivity of contents, and are becoming a part of users' lives. As media contents consumers move from traditional media to SNS, marketing communication activities are rapidly adapting to leading SNS platforms such as Facebook. This study compares how users perceive four advertisement attributes in each SNS, focusing on Facebook, Instagram, Kakao Story, and Twitter, where the media content creation and consumption systems are relatively similar to each other. The impact on eWOM intention was identified. In addition, we discussed effective SNS operation.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.51-55
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• 2017

In this paper, we designed a LBS-based smart platform for Lifelog service that can utilize the other's lifelog information. The conventional Lifelog service means that the system records the daily activities of the smart device user so the user can retrieve the early-recorded information later. The proposed Lifelog service platform uses the GPS/UFID location information and the various information extracted from the image as the lifelog data. Further, the proposed Lifelog platform using DB can provide the user with the Lifelog data recorded by the other service user. The system usually provide the other's Lifelog data within the 500m distance from the user and the range of distance can be adjustable. The proposed smart platform based on image recognition for Lifelog can acquire the image from the smart device directly and perform the various image recognition processing to produce the useful image attributes. And it can store the location information, image data, image attributes and the relevant web informations on the database that can be retrieved by the other use's request. The attributes stored and managed in the image information database consist of the followings: Object ID, the image type, the capture time and the image GPS coordinates. The image type attribute has the following values: the mountain, the sea, the street, the front of building, the inside of building and the portrait. The captured image can be classified into the above image type by the pattern matching image processing techniques and the user's direct selection as well. In case of the portrait-attribute, we can choose the multiple sub-attribute values from the shirt, pant, dress and accessory sub-attributes. Managing the Lifelog data in the database, the system can provide the user with the useful additional services like a path finding to the location of the other service user's Lifelog data and information.

• Speech Sciences
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• v.10 no.1
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• pp.71-84
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• 2003

In the acoustic modeling for large vocabulary speech recognition, a sparse data problem caused by a huge number of context-dependent (CD) models usually leads the estimated models to being unreliable. In this paper, we develop a new clustering method based on the C45 decision-tree learning algorithm that effectively encapsulates the CD modeling. The proposed scheme essentially constructs a supervised decision rule and applies over the pre-clustered triphones using the C45 algorithm, which is known to effectively search through the attributes of the training instances and extract the attribute that best separates the given examples. In particular, the data driven method is used as a clustering algorithm while its result is used as the learning target of the C45 algorithm. This scheme has been shown to be effective particularly over the database of low unknown-context ratio in terms of recognition performance. For speaker-independent, task-independent continuous speech recognition task, the proposed method reduced the percent accuracy WER by 3.93% compared to the existing rule-based methods.

• Journal of Intelligence and Information Systems
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• v.2 no.1
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• pp.45-58
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• 1996

This paper describes an a, pp.oach to recognizing composite features of prismatic parts. AAG (Attribute Adjacency Graph) is adopted as the basis of describing basic feature, but it is extended to enhance the expressive power of AAG by adding face type, angles between faces and normal vectors. Our a, pp.oach is called Extended AAG (EAAG). To simplify the recognition procedure, feature classification tree is built using the graph types of EEA and the number of EAD's. Algorithms to find open faces and dimensions of features are exemplified and used in decomposing composite feature. The processing sequence of recognized features is automatically determined during the decomposition process of composite features.

• Fashion & Textile Research Journal
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• v.21 no.3
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• pp.288-299
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• 2019

This study examined trends in model perceptions in the Asian fashion industry through a survey on the current status of using models, model attributes, and image recognition for companies and brands participating in the Seoul Fashion Week and Hong Kong Fashion Week. The results of the study are as follows. First, an examination of the races of models used for public relations by clothing and accessory companies indicated that the use of Asian and black models was lower than white models. Second, intimacy, reliability, similarity, and professionalism were derived as attributes for a public relation model. Among these factors, only 'intimacy' showed a difference between the countries. Third, Seoul Fashion Week participants gave the highest marks for the strong individuality of the models used for their brands; however, participants in the Hong Kong Fashion Week most appreciated suitability with products and professional appearance. Fourth, the different trends of model image recognition were shown through various analysis results by country or race, in which Seoul Fashion Week participants highly perceived the global and luxurious image of white models, and were generally highly satisfied with the models. In terms of the Hong Kong Fashion Week, Asian models tended to be perceived as a more casual image, and the participants held contributions to brand recognition as the most significant factor when using Asian models.

• Annual Conference on Human and Language Technology
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• 1989.10a
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• pp.197-202
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• 1989

한글에서 발생하는 자소의 접촉에 의한 오인식을 해결하기 위하여, 접촉점을 중심으로 원소를 변환하여, 확장 가능한 구조를 모두 검증하고, 수락된 후보패턴에 대하여 가장 근접한 패턴 클래스로 할당하는 한글 인식방법을 제안한다. 프로그램드 배열운법을 이용하여 화소의 2차원 배열에서 입력패턴을 인식하고, PEACE(Primitive-Extraction and Attribute-Computation Embeded ) 파싱을 이용하여, 원소(primitive)의 추출과 숙성 (attribute)의 계산을 구문분석 과정에 통합하고, 전체 시스템이 동적인 구조를 갖게하여, 1차원 스트링으로의 변환에 따르는 패턴의 변형과 부가적인 노력을 억제한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.166-168
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• 2012

바이오 문헌으로부터의 의미 있는 객체 추출 및 상호작용 관계 추출은 수 많은 바이오 문헌으로부터 유용한 정보를 얻기 위한 필수적인 과정이다. 특히 문헌으로부터 유전자 또는 단백질 이름과 같은 바이오 객체를 정확하게 인지하는 것은 새로운 객체인식의 어려움과 객체를 찾기 위한 특징 패턴의 다양성으로 인해 도전적인 과제로 남아있다. 본 논문에서는 전처리 과정을 거친 문헌 데이터로부터 12개의 의미 있는 속성들을 선택하였다. 선택된 속성에 데이터마이닝 기법중 하나인 속성 추출 기법을 적용하여 객체를 분류하는데 있어 의미 있는 속성들을 추출하였다. 특징 추출 방법과 분류 알고리즘이 분류 성능에 미치는 영향을 평가하기 위해 각 방법의 정확도를 사용하여 분류 성능을 비교였으며, Gain Ratio Attribute Evaluation과 Symmetrical Uncertainty Attribute Evaluation 기법에 의해 추출된 속성이 가장 정확한 분류 성능을 보여주었다.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1171-1178
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• 2019

This study proposes a deep neural network model based on an encoder-decoder structure for visual dialogs. Ongoing linguistic understanding of the dialog history and context is important to generate correct answers to questions in visual dialogs followed by questions and answers regarding images. Nevertheless, in many cases, a visual understanding that can identify scenes or object attributes contained in images is beneficial. Hence, in the proposed model, by employing a separate person detector and an attribute recognizer in addition to visual features extracted from the entire input image at the encoding stage using a convolutional neural network, we emphasize attributes, such as gender, age, and dress concept of the people in the corresponding image and use them to generate answers. The results of the experiments conducted using VisDial v0.9, a large benchmark dataset, confirmed that the proposed model performed well.

• Journal of the Economic Geographical Society of Korea
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• v.13 no.2
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• pp.253-269
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• 2010

This study analyzed image similarity, attribute recognition, and preference by multidimensional scaling. The analyses were carried out by 10 spa destinations (Deoksan, Bugok, Onyang, Yuseong, Suanbo, Bomun, Dongrae, Asan, Dogo, Haeundae) in Korea. The results were as follows: First, according to the analyses of image similarity of spa destinations, 'Haeundae, Dongrae and Bomun,' 'Dogo, Onyang, Asan,' and 'Deoksan, Suanbo, Bugok,' made similar image groups separately. However, Yuseong had different image from the other spa destinations in the above. Second, according to the analyses of attribute recognition of spa destinations, Deoksan and Bugok had more competitive ability in terms of 'the incidental facilities of spa destinations, 'Yuseong, Onyang, Asan, and Dogo' showed high competitiveness in terms of 'accessibility of spa destination' and 'tourism conditions.' Haeundae, Dongrae, and Suanbo had weak competitiveness in terms of 'the accessibility of spa destinations.' Third, according to the analyses of preference about spa destinations based on different job groups, office workers had a preference for Yuseong and Bugok, professional workers for Bomun, the people engaged in the farming, fishing, livestock raising and housewives for Haeundae and Dongrae, government officials, students, factory workers, the people living on a pension for Onyang, Deoksan and Dogo, and the self-employed for Suanbo. In conclusion, according to the analyses of spa destination preference based on different residence groups, residents of Seoul, Incheon, Gyunggi province, Gangwon province, Daejeon, Chungcheong province and Jeolla province had a preference for Yuseong, Suanbo, Onyang, Deoksan, and Asan and the residents of Daegu, Gyungsang province, Busan, Ulsan for Bugok, Bomun, and Haeundae.