• Journal of Science of Art and Design
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• v.8
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• pp.129-159
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• 2005

Web sites have become one of most important factor for sales products as well as advertising communications in these days. So numerous web sites have been developed for corporations and brands. It is not easy to getting more attention as a prominent web site expression among various types of numerous web sites. Due to the voluminous expansion of visual communications and the change of the media. new advertising creative must be needed for serving to differentiate the message, inviting audiences to participate more positively in Web site communications. This thesis aims at reviewing images and semiotics for analyzing web sites. And this thesis is about the significations of web sites for some of supreme brands. Chapter I describes the aim of this thesis about the signification of web sites, especially concentrate on the intro-pages of worldwide supreme brands. such as Chanel, Louis Vuitton, Yves Saint Laurent, Prada, and Burberry. And Chapter II introduces the general concept of Image and Semiotics. Chapter III deals with the signification of the web sites with introducing semiotic methods such as the theory of R. Barthes. Chapter IV discusses the signification of Images of web sites as an advertising creative talking into consideration of semiotic theories. And this thesis analyze almost all visual images and verbal message by the theory of R. Barthes. In this matrix, a. particular image of web site can be analyzed into its basic structure of pictorial and word elements , i. e., into the representations the viewer uses and identifies. It's my belief that one of aesthetic engineering approaches such as Semantic Differential Method and semiotic approaches such as the Interpretant Matrix for advertising design images provide basic methods which is about defining the process of constructing and coding the advertising images as well as analyzing and decoding advertising expressions. So I suggest these kinds of studies on the images of web sites as well as advertising design images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.310-312
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• 2019

Many technologies developed by the Fourth Industrial Revolution. These technologies are available to many users over the Web using the Web standard HTML5. As the content offered on the web increases, the number of users using the web increases and the importance of web speed increases. Because users expect the web page to load faster, as the web page loading speed increases, users will leave the page. That is, web page loading rates and page departure rates are proportional. Therefore, it is necessary to speed up web page loading by increasing the speed at which content is provided. In this paper, let's check through an experiment how it can be provided faster when providing images on the Web with regard to images that are one of the contents provided through the Web. Based on the results of these experiments, we want to identify faster ways to provider images over the web and provide images in that way to reduce page departure rates and provide more user-friendly services.

• Journal of Internet Computing and Services
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• v.11 no.3
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• pp.15-24
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• 2010

In this paper, we propose an image classification which combines semantic relations of tags with contents of images to improve the satisfaction of image retrieval on application domains as huge image sharing sites. To make good use of image retrieval or classification algorithms on huge image sharing sites as Flickr, they are applicable to real tagged Web images. To classify the Web images by 'bag of visual word' based image content, our algorithm includes training the category model by utilizing the preliminary retrieved images with semantically related tags as training data and classifying the test images based on PLSA. In the experimental results on the Flickr Web images, the proposed method produced the better precision and recall rates than those from the existing method using tag information.

• Convergence Security Journal
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• v.16 no.1
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• pp.81-87
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• 2016

In this paper, we propose a forgery/falsification detection technique of web site using the images. The proposed system captures images of the web site when a user accesses to the forgery/falsification web site that has the financial information deodorizing purpose. The captured images are compared with those of normal web site images to detect forgery/falsification. The proposed system calculates similarity factor of normal site image with captured one to detect whether the site is normal or not. If it is determined as normal, analysis procedure is finished. But if it is determined as abnormal, a message informs the user to prevent additional financial information spill and further accidents from the forgery web site.

• Journal of the Korean Home Economics Association
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• v.41 no.8
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• pp.159-178
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• 2003

The purpose of this research is to analyze the characteristics of colors and color images on fashion web sites, and to provide efficient color informatiom which is useful in color planning and is suitable for brand image on fashion web sites.216 color sample used by 48 fashion web sites were collected and analyzed. The results of this study are as follows; First, dominant colors on fashion web sites are neutral color such as white, gray, black and warm colors such as red, yellow red, yellow. Except blue, cool colors show low usage ratio. Second, the color tones of vivid, strong, light, dull, dark, dark grayish were shown in order. Third, the color images on fashion web sites are casual, modem, romantic, natural, elegant, chic, classic, dandy, pretty, clear, cool casual, dynamic, gorgeous, ethnic and formal.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• Journal of the Korea Society of Computer and Information
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• v.6 no.4
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• pp.51-59
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• 2001

As internet activates, web sites that supply images harmful to the emotion of youth are overflowing rapidly. Chances that the youth approach to the harmful sites are increasing, and then the emotion of youth is damaged seriously. In this paper, we present the system that distinguish harmful ones from images in the web documents of user-accessed URLs and output the document after blocking images harmful to the youth. As the results of the experiments about performance of the web-images blocking system, we found the utility factor of blocking harmful images of the proposed system is 89.6％ in the full nudity 70.1％ in the half nudity, and the error rate is 2.4％ in the face images.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.699-706
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• 2007

This article is an approach to improving the clustering of Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering algorithm, a self-organizing map (SOM) proposed by Kohonen is used. To evaluate the clustering efficiencies of SOMs, we propose a simple but effective measure indicating the accumulativeness of same class images and the perplexities of class distributions. Our approach is to advance the existing measures through defining and using new measures accumulativeness on the most superior clustering node and concentricity to evaluate clustering efficiencies of SOMs. The experimental results show that the high-level text features are more useful in SOM-based Web image clustering.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.355-366
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• 2002

The web is one of the most plentiful sources of images. The web has an immediate need for image processing technology in Java. This paper provides a practical introduction to statistical image processing using Java on the web. The paper describes how images are represented in Java and deals with four image processing operations based on basic statistical methods: point processing, spatial filtering, edge detection and image segmentation.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.4
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• pp.26-31
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• 2004

Due to the recent explosive progress of Web, We can easily access a large number of images from m. In this paper, we describe our approach of developing a general purpose content based image retrieval system over the H using a Web agent. The Web agent extracts text information of images from the links and file contents in HTML. The proposed system retrieves the images from database using the query by sketch and the query by example on Web browser. Experimental results demonstrate the effectiveness of the new approach.