• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.481-484
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• 2024

본 논문에서는 레고(LEGO®) 조립 설명서를 생성하기 위해 딥러닝을 이용한 조립 및 설명서 생성 시스템을 제안한다. 이 시스템은 사용자가 제공한 단일 이미지를 기반으로 레고 조립 설명서를 자동 생성한다. 해당 시스템은 딥러닝 기반 이미지 분할 기술을 활용하여 물체를 배경으로부터 분리하고 이를 통해 조립 설명서를 생성하는 과정을 포함하며, 조립을 위한 알고리즘을 새로 설계하였다. 이 시스템은 기존 레고 제품의 한계를 극복하고, 사용자에게 주어진 부품으로 다양한 모델을 자유롭게 조립할 수 있게 한다. 또한, 복잡한 레고 조립 과정을 간소화하고, 조립의 장벽을 낮추는 데 도움을 준다.

• ICROS
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• v.21 no.4
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• pp.21-26
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• 2015

지능형 시스템의 수요가 증가하면서 영상인식의 중요성이 부각되고 있다. 사람이 직접 물체 인식 과정을 모델링하는 방식을 넘어 최근에는 기계학습을 이용하여 이를 자동화하는 방법이 주를 이루고 있다. 그 중 딥러닝은 빅데이터를 활용하는 각종 분야에서 놀라운 성능을 보이며 기계학습 수준을 한 단계 진화시킨 기술로 평가 받고 있으며 영상 인식의 다양한 분야에서 응용되고 있다. 본 글에서는 딥러닝을 이용한 물체 검출 기법의 동향을 살펴보고 이를 차량 전면부 인식에 적용한 사례를 소개한다.

• The Journal of Korean Association of Computer Education
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• v.11 no.2
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• pp.89-98
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• 2008

Providing appropriate interactions between learner and e- Learning system is an essential factor of a successful e-Learning system. Although many interaction functions are employed in multimedia Web-based Instruction content, learner experience a lack of similar feedbacks from educators in real- time due to the limitation of Human-Computer Interaction techniques. In this paper, an emotion recognition system via learner facial expressions has been developed and applied to a tutoring system. As human educators do, the system observes learners' emotions from facial expressions and provides any or all pertinent feedback. And various feedbacks can bring to motivations and get rid of isolation from e-Learning environments by oneself. The test results showed that this system may provide significant improvement in terms of interesting and educational achievement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.6
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• pp.502-505
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• 2005

According to use of a multimedia content being increased in an e-learning, a size deviation of a content to provide in an e-teaming system is increased. It is becoming a factor to drop efficiency of education because this makes a deviation of response time on an e-learning user. Therefore, studies about a deviation improvement of user response speed is necessary in the e-learning system that used a multimedia content. In this study, we designe the hybrid e-teaming system that used multi-layed structire. A proposed system is based on a characteristics of media and size of a content that a multimedia data had. Also, it proved superiority of performance through experimentation.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.157-160
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• 2006

최근 e-러닝 산업 및 기술에서 큰 화두는 디지털 융합과 현상이라고 할 수 있으며, 이러한 융합화 시대를 향한 진화의 핵심적인 요구사항은 OSMU 이다. 현재까지 e-러닝 산업은 표준화 활동을 통해 디지털 융합화를 실현하고 있으며, 미국 ADL의 SCORM이 사실상의 표준으로 인식되고 있다. 하지만 기존 웹 기반의 e-러닝 환경은 학습을 할 때 컴퓨터에 의존함으로써 실질적인 디지털 격차를 극복하기에 한계가 있다. 이에 본 논문에서는 보다 실생활에 근접한 DiTV용 T-러닝 학습 환경에의 적용을 위하여 이미 작성된 SCORM 기반의 학습 콘텐츠 메타데이터를 DiTV용 TV-Anytime 메타데이터로 변환하여 상호운용성, 재사용성 및 고 이용성 등을 가능하게 하는 시스템의 설계를 제안하고자 한다. 이 시스템을 통하여 PC 에 익숙하지 못한 사람들을 DiTV 앞에서 더욱 편한 학습 기회를 제공할 수 있을 것이다.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.151-157
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• 2009

A lot of E-Learning system is supplying the existent item difficulty based learning information to learner. And learner is doing learning contents according to the fixed learning course. It is difficult for learner to get efficient learning effect. Because learner has to belong to fixed item difficulty and learning course even thought learner has different degree that understand studying in learning course. This research proposed the learner adaptive E-learning system that is able to control the item difficulty and learning course to analyze the understanding degree of learner in learning course. In this result, learner is able to improve learning effect to get rid of fixed learning course using bi-directed learning such as off-line learning.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.235-242
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• 2013

Reputation systems aggregate users' feedback after the completion of a transaction and compute the "reputation" of products, services, or providers, which can assist other users in decision-making in the future. With the rapid growth of online e-Learning content providing services, a suitable reputation system for more credible e-Learning content delivery has become important and is essential if educational content providers are to remain competitive. Most existing reputation systems focus on generating ratings only for user reputation; they fail to consider the reputations of products or services(item reputation). However, it is essential for B2C e-Learning services to have a reliable reputation rating mechanism for items since they offer guidance for decision-making by presenting the ranks or ratings of e-Learning content items. To overcome this problem, we propose a novel collaborative filtering based reputation rating method. Collaborative filtering, one of the most successful recommendation methods, can be used to improve a reputation system. In this method, dual information sources are formed with groups of co-oriented users and expert users and to adapt it to the reputation rating mechanism. We have evaluated its performance experimentally by comparing various reputation systems.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.150-160
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• 2007

In the actual classroom the so-called flow learning is able to motivate the students through face-to-face feedback, and to meet their needs for educational achievement. By contrast, the so-called e-learning method falls short of the satisfactory level of real-life interaction, which makes many learners drop out or give up on their learning. In order to better the e-learning environment, this study presents a dialogue-based feedback system that improves the flow learning of the learners' in the classroom. This newly developed system was applied at the actual school. The result is that the experimented group improved its flow learning, compared with the controlled group. In the former group, each individual showed some consciousness of objective and challenge following the concrete feedback. That is to say, this system enhances the attitude of an active participation and induces the flow learning, thanks to the dialogue-based feedback and the sustained interest in learning. In conclusion, the significance of this study lies in suggesting the direction of a new learning method development in the e-learning environment.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.211-217
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• 2011

Recent IT (information technology) environmental changes, such as emerging social network services or increasing user participation in multimedia environment, have made it necessary for e-learning systems to undergo changes in various ways. Metadata is an agreement for interoperability between different systems. The standardization of metadata for e-learning system has been driven by some domestic and international organizations, but applying diverse environmental changes into the design of e-learning metadata is in dire need. In this paper, we present a methodology for the analysis and design of modeling e-learning metadata and elicit the design requirements, on the basis of the metadata standard KEM 3.0, about the elements that are expected to be needed in future e-learning systems. Based on the requirements from the analysis, we present the three-layer model for classifying the requirements by the importance of metadata elements per Kana Model. An intelligent e-learning system is to be developed based on the proposed modeling design, which we hope to influence the development of an international standard in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.960-963
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• 2013

By the rapid development ICTs, education is entering into a smart learning. Learners are put down the paper book, are learning by using a various smart devices, and at this moment emerged that learning system each of which contains numerous platforms. Platform-specific systems require a lot of time and money to applicable to heterogeneous platforms, and This phenomenon is exacerbated if system has a lot of learning contents. Learning system that supports cross-platform is needed for reduce the unnecessary waste of resources and provide effective learning content. In order to achieve this, the research must be preceded by a database model that numerous of existing learning content can be integrated without any unnecessary redundant. In this paper, suggests Ontology-based metadata model that can be integrate existing learning content as an alternative to database, and through this, Design and Implementation of smart learning system that support Heterogeneous platforms.