• 한국멀티미디어학회논문지
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• 제17권12호
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• pp.1446-1452
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• 2014

Existing LDA uses the transform matrix that maximizes distance between classes. So we have to convert from an image to one-dimensional vector as training vector. However, in 2D-LDA, we can directly use two-dimensional image itself as training matrix, so that the classification performance can be enhanced about 20% comparing LDA, since the training matrix preserves the spatial information of two-dimensional image. However 2D-LDA uses same calculation schema for transformation matrix and therefore both LDA and 2D-LDA has the heteroscedastic problem which means that the class classification cannot obtain beneficial information of spatial distances of class clusters since LDA uses only data correlation-based covariance matrix of the training data without any reference to distances between classes. In this paper, we propose a new method to apply training matrix of 2D-LDA by using WPS-LDA idea that calculates the reciprocal of distance between classes and apply this weight to between class scatter matrix. The experimental result shows that the discriminating power of proposed 2D-LDA with weighted between class scatter has been improved up to 2% than original 2D-LDA. This method has good performance, especially when the distance between two classes is very close and the dimension of projection axis is low.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.153-159
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• 2022

The article discusses the use of smart technologies in the training of future specialists. Today, learning using smart technologies is becoming a new educational standard, where information is presented in a logical sequence, computer training systems have powerful functions for the educational process. The functions of smart technologies are highlighted. It is noted that smart technologies are successfully used in the field of education and professional training. The concept of "smart education" is characterized. Smart education is an educational paradigm that underlies a new type of education system. The implementation of the smart education paradigm is aimed at the process of obtaining competencies and competencies for flexible and adapted interaction with the social, economic and technological environment. Smart education should ensure that the benefits of the global information society can be used to meet educational needs and interests. A special place is occupied by computer-based educational multimedia systems that allow you to deepen your knowledge, reduce the duration of training, and increase the number of students per teacher. The main principles of smart education are highlighted. Improving the efficiency of training in a modern higher education institution is impossible without the introduction of smart technologies in the organization of the educational process.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2019년도 하계학술대회
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• pp.102-105
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• 2019

In the classical single-image super-resolution (SISR) reconstruction method using convolutional neural networks, the extracted features are not fully utilized, and the training time is too long. Aiming at the above problems, we proposed an improved SISR method based on a residual network. Our proposed method uses a feature fusion technology based on improved residual blocks. The advantage of this method is the ability to fully and effectively utilize the features extracted from the shallow layers. In addition, we can see that the feature fusion can adaptively preserve the information from current and previous residual blocks and stabilize the training for deeper network. And we use the global residual learning to make network training easier. The experimental results show that the proposed method gets better performance than classic reconstruction methods.

• 인터넷정보학회논문지
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• 제20권4호
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• pp.47-53
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• 2019

일반적으로 어지럼증은 여러 가지 복합적인 원인에 의해서 발생하지만 그 중에서 신경계에 속하는 전정계통의 기능 장애에 의한 증상이 가장 환자에게 심한 증상으로 다가오며, 구역질과 구토를 동반하게 된다. 이러한 어지럼증에 대한 치료는 약물요법, 수술요법, 재활치료 등이 있으며, 약물요법이나 수술요법은 대체적으로 후유증의 위험 때문에 재활치료요법인 전정재활훈련을 많이 시행하고 있다. 전정재활훈련은 안구훈련, 자세안정훈련, 보행훈련 등이 있는데 그 중 보행훈련은 의사 또는 전문치료사의 감독하에 일정한 공간에서 진행되므로 시간적, 공간적 부담이 가중되어 환자들이 훈련을 진행기 불편한 단점을 가진다. 이를 해결하고자 본 논문에서는 증강현실 기술을 활용해 사용자가 직접 보행재활훈련을 진행 할 수 있는 보행훈련 콘텐츠를 구현하였다. 추후 어지럼증 환자를 대상으로 한 임상시험을 통해 의료 환경에서 사용 가능한 어지럼증 재활 콘텐츠로 활용 가능할 것으로 기대한다.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.328-335
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• 2021

In the era of 'Untact', virtual reality-based job training platforms are actively being used as part of non-face-to-face education for students with developmental disabilities. Because the people with developmental disabilities may lack sufficient cognitive abilities, it is difficult to conduct untact training seamlessly without the help of a third party. Therefore, it is necessary for training programs to identify the right timing to provide help so that the training can be continued. This research analyzed the visual attention of students with developmental disabilities in virtual reality-based job training program in order to determine the point of time when an intervention is required by the trainee. Results showed that students who completed the mission tended to have intense visual attention on a small number of objects for a certain period of time; the visual attention of the students who failed tended to shift erratically among multiple objects.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.120-124
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• 2021

Recently, human attribute recognition (HAR) attracts a lot of attention due to its wide application in video surveillance systems. Recent deep-learning-based solutions for HAR require time-consuming training processes. In this paper, we propose a post-processing technique that utilizes the historical video frames to improve prediction results without invoking re-training or modifying existing deep-learning-based classifiers. Experiment results on a large-scale benchmark dataset show the effectiveness of our proposed method.

• 한국컴퓨터정보학회논문지
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• 제25권9호
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• pp.71-80
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• 2020

사회가 초연결 사회가 되어 갈수록 우리는 더 많은 사이버 보안 전문가들이 필요하다. 이를 위해 본 논문에서는 실제 사이버 공격에 대한 분석결과와 MITRE ATT&CK 프레임워크를 바탕으로 사이버 모의 위협을 모델링하고 실제 사이버 보안 훈련 시스템에서 모의 된 사이버 위협을 생성할 수 있는 CyTEA를 개발하였다. 모의 된 사이버 위협이 실제 사이버 위협 수준의 유효성을 갖는지를 확인하기 위해 절차적, 환경적, 결과적 유사성을 기준으로 모의 수준을 알아보고 또 실제 사이버 보안 훈련 시스템에서 모의 위협을 실행하면서 방어훈련 시 예상되는 위협의 실제 위협실행 결과와 모의 위협의 실행 결과가 동일하여 실제 사이버 위협에 준하는 훈련을 가능함을 확인하였다.

• 농촌지도와개발
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• 제8권1호
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• pp.1-14
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• 2001

e-Learning has brought dramatic changes in education system for many companies in Korea. Many researchers and practitioners believe that e-Learning will be the main educational system for every companies in the world. e-Learning is an alternative education system, which includes computer based learning, web based learning, virtual classroom, and distance learning. e-learning has been expected to impact every educational sectors including Extension services. This study intends to identify and suggest some implications for successful e-Learning implementation of Extension education by investigating the successful factors of enterprises' e-Learning system, where outstanding results have be shown.

• 정보교육학회논문지
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• 제4권1호
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• pp.98-108
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• 2000

교원 연수에 있어서 웹을 기반으로 한 가상 연수가 앞으로 더욱 늘어날 전망이다. 그러나, 아직까지는 가상 연수는 하드웨어적인 시스템의 측면에서만 평가가 이루어져 왔고, 긍정적인 면만을 연구해 온 감이 없지 않다. 이제는 이러한 시스템 측면을 발전시켜가면서 몇몇 기관에서 선도적으로 시행한 가상 연수 프로그램의 문제점을 분석하고, 개선 방안을 찾아볼 시점이다. 하지만 각 연수 기관에서 이러한 운영상의 문제점들을 자체적으로 분석하고 있을 뿐 비교 평가할 기회가 없었다. 따라서 본 논문에서는 몇 개의 기관에서 시행한 웹 기반 가상 연수 운영에 대한 데이터를 입수하여 비교 분석하고, 문제점을 해결하기 위한 방안을 모색하고자 한다.