• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.322-329
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• 2017

Recently, the importance of personalized healthcare(wellness) services is increasing in the era of the 4th Industrial Revolution. However, the authoring of wellness contents fused with variety of contents and the study of the system which provides the customized recommendation are insufficient. In this paper, we proposes the recommendation service system for the customized convergence wellness contents. The proposed system makes to the wellness contents by the existing cultural/tourism/leisure contents and recommends the customized wellness contents based on a user's profile and the situation information such as location and weather. The proposed systems is expected to contribute to designing the innovative and new service models for the tailored wellness content.

• 한국멀티미디어학회논문지
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• 제22권2호
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• pp.250-259
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• 2019

Big data processing technology and artificial intelligence (AI) are increasingly attracting attention. Natural language processing is an important research area of artificial intelligence. In this paper, we use Korean news articles to extract topic distributions in documents and word distribution vectors in topics through LDA-based Topic Modeling. Then, we use Word2vec to vector words, and generate a weight matrix to derive the relevance SCORE considering the semantic relationship between the words. We propose a way to recommend documents in order of high score.

• 한국멀티미디어학회논문지
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• 제24권4호
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• pp.528-537
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• 2021

Face recognition has gained significant notice because of its application in many businesses: security, healthcare, and marketing. In this paper, we will present the recognition method using the combination of correlation filters (CF) and Support Vector Machine (SVM). Firstly, we evaluate the performance and compared four different correlation filters: minimum average correlation energy (MACE), maximum average correlation height (MACH), unconstrained minimum average correlation energy (UMACE), and optimal-tradeoff (OT). Secondly, we propose the machine learning approach by using the OT correlation filter for features extraction and SVM for classification. The numerical results on National Cheng Kung University (NCKU) and Pointing'04 face database show that the proposed method OT-SVM gets higher accuracy in face recognition compared to other machine learning methods. Our approach doesn't require graphics card to train the image. As a result, it could run well on a low hardware system like an embedded system.

• 한국멀티미디어학회논문지
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• 제24권6호
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• pp.745-752
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• 2021

In this paper, we propose a system that recognizes weed images using a classifier based on ResNeXt model. On the server of the proposed system, the ResNeXt model extracts the fine features of the weed images sent from the user and classifies it as one of the most similar weeds out of 21 species. And the classification result is delivered to the client and displayed on the smartphone screen through the application. The experimental results show that the proposed weed recognition system based on ResNeXt model is superior to existing methods and can be effectively applied in the real-world agriculture field.

• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1447-1453
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• 2020

In this paper, we propose a method for no-reference quality assessment of sports videos using 3D shearlet transform and deep residual neural networks. In the proposed method, 3D shearlet transform-based spatiotemporal features are extracted from the overlapped video blocks and applied to logistic regression concatenated with a deep residual neural network based on a conditional video block-wise constraint to learn the spatiotemporal correlation and predict the quality score. Our evaluation reveals that the proposed method predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1476-1485
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• 2020

Segmenting OCT retinal images into layers is important to diagnose and understand the progression of retinal diseases or identify potential symptoms. The task of manually identifying these layers is a difficult task that requires a lot of time and effort even for medical professionals, and therefore, various studies are being conducted to automate this using deep learning technologies. In this paper, we use cGAN-based neural network to automatically segmenting OCT retinal images into seven terrain-type regions defined by six layer boundaries. The network is composed of a Segnet-based generator model and a discriminator model. We also proposed a dynamic programming algorithm for refining the outputs of the network. We performed experiments using public OCT image data set and compared its performance with the Segnet-only version of the network. The experimental results show that the cGAN-based network outperforms Segnet-only version.

• 한국멀티미디어학회논문지
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• 제25권3호
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• pp.468-475
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• 2022

Currently, fine dust forecast models are operated by dividing the country into 19 regions. Therefore, it is important to reduce the learning time and the number of models as well as accurate forecast performance to operate lots of forecast models. In this paper, we develop a categorical wide area model that outputs forecast results categorically and integrates the regions with similar regional characteristics. The proposed model improved the convergence rate by 223 times compared to the existing model, which outputs at a single concentration value, and reduced the number of forecast models by a third.

• ETRI Journal
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• 제28권5호
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• pp.561-573
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• 2006

In this paper, we present a practical implementation of the MPEG-21 multimedia framework for broadcasting and communication convergent services. MPEG-21 standard technology was exploited to build a convergent service framework. Using this framework, a service model and several scenarios have been successfully designed and implemented. In addition, interoperability, which is the main objective of a multimedia framework, especially in a convergent environment consisting of heterogeneous networks and various types of devices, has been addressed in detail. The experimental results show that the implemented test bed provides a next-generation multimedia service; that is, universal multimedia access (UMA), meeting the requirements of a broadcasting and communication convergent environment.

• Journal of information and communication convergence engineering
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• 제2권3호
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• pp.139-144
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• 2004

In order to transmit various types of multimedia data (i.e. voice, video, and data) over a wireless channel, the coding and modulation scheme needs to be flexible and capable of providing a variable quality of service, data rates, and latency. In this paper, we study a mobile multimedia COMA network combined with the concatenated Reed-Solomon/Rate Compatible Punctured Convolution code (RS/RCPC). Also, this paper propose the combination of concatenated RS/RCPC coder and COMA RAKE receiver for multimedia COMA traffic which can be sent over wireless channels. From the results, using a frequency selective Rayleigh fading channel model, it is shown that concatenated RS/RCPC coder at the wireless physical layer can be effective in providing reliable wireless multimedia CDMA network. And the proposed scheme that combine concatenated RS/RCPC coder and CDMA RAKE receiver provides a significant gain in the BER performance over multi-user interference and multipath frequency selective fading channels.

• 한국정보기술학회 영문논문지
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• 제10권1호
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• pp.85-97
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• 2020

As a solution to the rapid urbanization problem, interest in and use of personal mobility devices such as bicycles and electric kickboards are increasing, and accidents are also rising every year. In this study, a smart vest to prevent traffic accidents and promote safe driving of personal mobility users was designed and implemented. Unlike the existing products on the market that indicate directions using buttons, the smart vest designed and implemented in this study indicates the moving direction by shaking a bracelet and displays the direction by LEDs on the vest. Therefore, this product was designed and implemented to be safer and differentiated from other existing products.