• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2003년도 추계학술발표대회(하)
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• pp.844-847
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• 2003

정보화 시대가 발전함으로써 급속하게 변화하는 사회에 흐름에 따라 우리 교육 시스템에의 환경도 빠르게 변화, 발전하고 있다. 사회의 급속한 변화들과 더불어 정보기술의 발전은 교육환경에도 지대한 영향을 미치고, 이 환경에 발맞춰 학습교육시스템도 다양하게 발전하게 되었다. 즉, 정보통신 기술의 발달 결과로 웹을 기반으로 한 다양한 학습교육시스템들이 선보이고 있다. 웹 기반교육은 웹을 수단으로 하여 지식을 생성, 조직, 전파하는 교육방식이며, 구조화된 웹 문서를 가지고 다양한 상호작용을 통한 플랫폼을 구성하고 있다. 본 논문에서는 웹기반교육이 이루어지는 학습시스템의 다양한 플랫폼을 살펴보고 그에 대한 비교를 제안한다.

• 한국수학교육학회지시리즈A:수학교육
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• 제38권1호
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• pp.87-94
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• 1999

A multimedia CD title is developed for learning simple closed curve and Mobius band which are one of mathematics contents in the first grade of middle school. This title visualizes various figures through graphics and animations so that students can easily understand the relevant concepts and learn them with fun. It is shown that 88.6% of 30 sampled teachers are positive for the title and that 86.7% want to use it as a teaching tool in their classes.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.25-34
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• 2022

Today, further education of adults in the UK is one of the developing areas of continuing education. The Open University with distance learning, in the process of which innovative forms and methods based on computer and telecommunication technologies are used, is particularly successful in the organization of additional education of the adult population. The advantages of distance learning, multimedia - the latest information technologies, which provide the combination of graphic images, video, sound with the help of modern computer tools, are noted. The basic principles and forms underlying the technologies and forms of work with the elderly are defined. The international experience of implementing "Universities of the Third Age" is summarized. The most widespread approach in adult education in Great Britain is informational. The use of computer technologies motivates a new paradigm in educational methods and strategies, which requires new approaches, forms of learning, and innovative ways of delivering educational materials to adult learners. Information technologies have gained great popularity in such activities as distance learning, online learning, assistance in the education management system, development of programs and virtual textbooks in various subjects, online search for information for the educational process, computer testing of students' knowledge, creation of electronic libraries, formation of a single scientific electronic environment, publication of virtual magazines and newspapers on pedagogical topics, teleconferences, expansion of international cooperation in the field of Internet education. The information technology of synchronous distance learning "online" has gained considerable popularity in the educational process today. A promising direction is the use of multimedia technologies in educational activities to create a design of a virtual computer environment by decoding audiovisual information.

• 한국멀티미디어학회논문지
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• 제4권3호
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• pp.280-285
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• 2001

귀납적학습 알고리즘과 분석적학습 알고리즘을 결합한 지식기반인공신경망이 제안된 후, 이를 개선한 TopGen, TR-KBANN, THRE-KBANN과 같은 영역이론정련알고리즘이 제시되었다. 그러나 이들은 모두 KBANN과 같이 영역이론이 있을 경우에만 사용할 수 있다. 본 연구에서는 영역이론이 없이 예제만 있는 경우 KBANN으로 표기하는 알고리즘을 제시하였다. KBANN으로 표현된 영역 이론은 THRE-KBANN으로 정련화될 수 있다. 이 알고리즘을 귀납적 학습에서 사용하는 몇 개의 문제영역에 적용하여 실험한 결과 C4.5보다 좋은 성능을 나타냈다.

• 한국멀티미디어학회논문지
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• 제19권5호
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• pp.865-873
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• 2016

In recent years, Tracking-Learning-Detection(TLD) system has been widely used as a detection and tracking algorithm for vision sensors. While conventional algorithms are vulnerable to occlusion, and changes in illumination and appearances, TLD system is capable of robust tracking by conducting tracking, detection, and learning in real time. However, the detection and tracking algorithms of TLD system utilize rotation-variant features, and the margin of tracking error becomes greater when an object makes a full out-of-plane rotation. Thus, we propose a rotation-invariant TLD system(RI-TLD). we propose a simplified average orientation histogram and rotation matrix for a rotation inference algorithm. Experimental results with various tracking tests demonstrate the robustness and efficiency of the proposed system.

• Journal of Multimedia Information System
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• 제7권2호
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• pp.115-124
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• 2020

This paper is a study of deep learning among artificial intelligence technology which has been developing many technologies recently. Especially, I am talking about emotional computing that has been mentioned a lot recently during deep learning. Emotional computing, in other words, is a passive concept that is dominated by people who scientifically analyze human sensibilities and reflect them in product development or system design, and a more active concept that studies how devices and systems understand humans and communicate with people in different modes. This emotional signal extraction, sensitivity, and psychology recognition technology is defined as a technology to process, analyze, and recognize psycho-sensitivity based on micro-small, hyper-sensor technology, and sensitive signals and information that can be sensed by the active movement of the autonomic nervous system caused by human emotional changes in everyday life. Chapter 1 talks about overview and Chapter 2 shows related research. Chapter 3 shows the problems and models of real emotional computing and Chapter 4 shows this paper as a conclusion.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2012년도 춘계학술발표대회논문집
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• pp.414-416
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• 2012

정보통신 기술의 발달은 학습 환경에도 많은 변화를 가져왔다. U-learning을 비롯해 많은 학습 방법들이 과거의 제한된 장소에서의 학습이 아닌 언제 어디서든 자유롭게 학습할 수 있는 환경을 제공하고 있다. 본 연구에서는 QR-Code와 U-learning을 이용해 학습자들이 시공간의 제약 없이 학습 할 수 있는 환경을 학습의 장인 학교에 접목시켜 스마트 러닝이 가능하도록 하였다. 학습자들의 흥미를 이끌어내어 원하는 장소에서 원하는 시간에 언제든지 학습이 가능하도록 하여 학습 능력 향상을 기대하고 나아가 자기 주도적 학습에 도움이 될 것으로 기대된다.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2012년도 춘계학술발표대회논문집
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• pp.123-126
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• 2012

In general, there are 3 subjects of discussion in education field; namely past, present and future. Related with those facts, there is several information or knowledge that relatively hard to be presented in the real world. In this matter, digital content shows its contribution especially in the education field. Digital content can virtually represent the information or knowledge that seems to be difficult to be visualized in the real world before. In this project, researcher develops a mobile device's application that consist the skeleton's 3D virtual content. This application is expected to solve the above explained problem that usually appears during learning human skeleton in senior high-school's biology class. Besides, the application of digital content will make the learning process become easier because the student will have a visual learning tool. Last, the mobile device that is used in this prototype has offer an important beneficial namely mobility beneficial, so that the user can access the content anytime and anywhere.

• 한국멀티미디어학회논문지
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• 제9권6호
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• pp.762-772
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• 2006

Instance based learning algorithm is the best known lazy learner and has been successfully used in many areas such as pattern analysis, medical analysis, bioinformatics and internet applications. However, its feature weighting scheme is too naive that many other extensions are proposed. Our version of IB3 named as eXtended IBL (XIBL) improves feature weighting scheme by backward stepwise regression and its distance function by VDM family that avoids overestimating discrete valued attributes. Also, XIBL adopts leave-one-out as its noise filtering scheme. Experiments with common artificial domains show that XIBL is better than the original IBL in terms of accuracy and noise tolerance. XIBL is applied to two important applications - intrusion detection and spam mail filtering and the results are promising.

• 한국멀티미디어학회논문지
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• 제22권10호
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• pp.1133-1141
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• 2019

Most of the previous studies for bark recognition have focused on the extraction of LBP-like statistical features. Deep learning approach was not well studied because of the difficulty of acquiring large volume of bark image dataset. To overcome the bark dataset problem, this study utilizes the MobileNet which was trained with the ImageNet dataset. This study proposes two approaches. One is to extract features by the pixel-wise convolution and classify the features with SVM. The other is to tune the weights of the MobileNet by flexibly freezing layers. The experimental results with two public bark datasets, BarkTex and Trunk12, show that the proposed methods are effective in bark recognition. Especially the results of the flexible tunning method outperform state-of-the-art methods. In addition, it can be applied to mobile devices because the MobileNet is compact compared to other deep learning models.