• 제목/요약/키워드: 시각정보선택

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Object Detection Algorithm for Explaining Products to the Visually Impaired (시각장애인에게 상품을 안내하기 위한 객체 식별 알고리즘)

  • Park, Dong-Yeon;Lim, Soon-Bum
    • The Journal of the Korea Contents Association
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    • v.22 no.10
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    • pp.1-10
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    • 2022
  • Visually impaired people have very difficulty using retail stores due to the absence of braille information on products and any other support system. In this paper, we propose a basic algorithm for a system that recognizes products in retail stores and explains them as a voice. First, the deep learning model detects hand objects and product objects in the input image. Then, it finds a product object that most overlapping hand object by comparing the coordinate information of each detected object. We determine that this is a product selected by the user, and the system read the nutritional information of the product as Text-To-Speech. As a result of the evaluation, we confirmed a high performance of the learning model. The proposed algorithm can be actively used to build a system that supports the use of retail stores for the visually impaired.

A study on rethinking EDA in digital transformation era (DX 전환 환경에서 EDA에 대한 재고찰)

  • Seoung-gon Ko
    • The Korean Journal of Applied Statistics
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    • v.37 no.1
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    • pp.87-102
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    • 2024
  • Digital transformation refers to the process by which a company or organization changes or innovates its existing business model or sales activities using digital technology. This requires the use of various digital technologies - cloud computing, IoT, artificial intelligence, etc. - to strengthen competitiveness in the market, improve customer experience, and discover new businesses. In addition, in order to derive knowledge and insight about the market, customers, and production environment, it is necessary to select the right data, preprocess the data to an analyzable state, and establish the right process for systematic analysis suitable for the purpose. The usefulness of such digital data is determined by the importance of pre-processing and the correct application of exploratory data analysis (EDA), which is useful for information and hypothesis exploration and visualization of knowledge and insights. In this paper, we reexamine the philosophy and basic concepts of EDA and discuss key visualization information, information expression methods based on the grammar of graphics, and the ACCENT principle, which is the final visualization review standard, for effective visualization.

Analysis of Deep Learning-Based Pedestrian Environment Assessment Factors Using Urban Street View Images (도시 스트리트뷰 영상을 이용한 딥러닝 기반 보행환경 평가 요소 분석)

  • Ji-Yeon Hwang;Cheol-Ung Choi;Kwang-Woo Nam;Chang-Woo Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.6
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    • pp.45-52
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    • 2023
  • Recently, as the importance of walking in daily life has been emphasized, projects to guarantee walking rights and create a pedestrian environment are being promoted throughout the region. In previous studies, a pedestrian environment assessment was conducted using Jeonju-si road images, and an image comparison pair data set was constructed. However, data sets expressed in numbers have difficulty in generalizing the judgment criteria of pedestrian environment assessors or visually identifying the pedestrian environment preferred by pedestrians. Therefore, this study proposes a method to interpret the results of the pedestrian environment assessment through data visualization by building a web application. According to the semantic segmentation result of analyzing the walking environment components that affect pedestrian environment assessors, it was confirmed that pedestrians did not prefer environments with a lot of "earth" and "grass," and preferred environments with "signboards" and "sidewalks." The proposed study is expected to identify and analyze the results randomly selected by participants in the future pedestrian environment evaluation, and believed that more improved accuracy can be obtained by pre-processing the data purification process.

A Reduction Method of Over-Segmented Regions at Image Segmentation based on Homogeneity Threshold (동질성 문턱 값 기반 영상분할에서 과분할 영역 축소 방법)

  • Han, Gi-Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.55-68
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    • 2012
  • In this paper, we propose a novel method to solve the problem of excessive segmentation out of the method of segmenting regions from an image using Homogeneity Threshold($H_T$). The algorithm of the previous image segmentation based on $H_T$ was carried out region growth by using only the center pixel of selected window. Therefore it was caused resulting in excessive segmented regions. However, before carrying region growth, the proposed method first of all finds out whether the selected window is homogeneity or not. Subsequently, if the selected window is homogeneity it carries out region growth using the total pixels of selected window. But if the selected window is not homogeneity, it carries out region growth using only the center pixel of selected window. So, the method can reduce remarkably the number of excessive segmented regions of image segmentation based on $H_T$. In order to show the validity of the proposed method, we carried out multiple experiments to compare the proposed method with previous method in same environment and conditions. As the results, the proposed method can reduce the number of segmented regions above 40% and doesn't make any difference in the quality of visual image when we compare with previous method. Especially, when we compare the image united with regions of descending order by size of segmented regions in experimentation with the previous method, even though the united image has regions more than 1,000, we can't recognize what the image means. However, in the proposed method, even though image is united by segmented regions less than 10, we can recognize what the image is. For these reason, we expect that the proposed method will be utilized in various fields, such as the extraction of objects, the retrieval of informations from the image, research for anatomy, biology, image visualization, and animation and so on.

Development and Implementation of Commodity Data Catalog for E-Business (E-비즈니스를 위한 물품 데이터 카탈로그 구현 및 개발)

  • 윤호군;김선영;허우나;강성화;장선형;정화영
    • Proceedings of the Korea Database Society Conference
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    • 2000.11a
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    • pp.127-130
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    • 2000
  • 웹(Web)의 발달로 구매자들은 물건을 구매하기 위하여 직접 매장을 찾지 않고도 인터넷을 통한 각 쇼핑몰에서 제품이나 구매에 관한 정보 서비스를 바탕으로 원하는 제품의 정보를 얻고 제품을 선택해서 구매할 수 있게 되었다. 따라서, 제품의 구매를 결정함에 있어 가장 중요한 요소는 원하는 제품에 칠한 정보에 보다 빠르게 접근하고 정확한 정보를 입수하는 것이다. 이에 따라, 구매자들에게 보다 확실한 제품 정보를 제공하기 위한 효과적인 카탈로그를 구현 및 개발하려는 노력은 다각도로 진행되고있다. 그러나, 기존의 카탈로그는 단순한 텍스트 형식의 문서이며 제품 정보도 너무 빈약해 사용자가 제품에 대한 확실한 정보를 얻기 힘들다. 따라서, 본 논문에서는 사용자가 보다 많은 정보를 쉽게 접할 수 있도록 시각적인 제품정보와 함께 해당 제품정보에 관한 설명을 음성으로 지원하였다. 즉, 기존의 정적인 제품정보 화면에서 음성만을 지원하는 것이 아닌 제품에 관한 정보를 슬라이드 쇼 형태로 제공함으로써 제품에 관한 흥미유발과 구매욕구를 높일 수 있다.

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Efficient Tomography System of Electron Microscopy using Selective Filtering (선택적 Filtering을 이용한 효율적 전자현미경 Electron Tomography 시스템)

  • Jung, Won-Goo;Cho, Hye-Jin;Park, Seong Oak;Chae, Hee-Su;Je, A-Reum;Lee, Kyoung Hwan;Jung, Hyun Suk;Kweon, Hee-Seok
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.11a
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    • pp.395-396
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    • 2009
  • Electron tomography를 이용한 3차원적 영상 시각화는 electron microscopy를 통해 하나의 실험 대상으로부터 연속된 이미지를 생산함으로써 이루어진다. 이미지 데이터 내부에는 대용량의 정보값을 포함하고 있어 3차원 구조물로의 변환이 가능하다. electron tomography 작업 과정 중 고해상도 원본 이미지에 pattern recognition 알고리즘이 적용된 필터링을 적용하면 실험에 필요한 데이터의 정보 손실을 최소화한 상태에서 electron tomography 시스템의 효율성을 높일 수 있다. 또한 tomographic econstruction이 진행되는 각 단계에 hanning windowing을 적용하면 불필요한 정보 값이나 노이즈 등을 효과적으로 제거할 수 있다. 윤곽선 데이터의 효과적 활용을 위하여 sobel 필터 처리를 할 경우 관찰하고자 하는 대상의 윤곽선 특징을 뚜렷하게 시각화 할 수 있었다. 본 연구를 통하여 데이터의 시각화 과정에서 실험의 신뢰성 확보를 위해 원본 이미지를 기반으로 하는 tomogram과 필터링을 적용한 tomogram을 비교하여 최종 결과물의 정확도를 높이고, electron tomography를 통한 결과물의 질적 향상을 유도할 수 있음을 확인하였다.

Comparison of model selection criteria in graphical LASSO (그래프 LASSO에서 모형선택기준의 비교)

  • Ahn, Hyeongseok;Park, Changyi
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.881-891
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    • 2014
  • Graphical models can be used as an intuitive tool for modeling a complex stochastic system with a large number of variables related each other because the conditional independence between random variables can be visualized as a network. Graphical least absolute shrinkage and selection operator (LASSO) is considered to be effective in avoiding overfitting in the estimation of Gaussian graphical models for high dimensional data. In this paper, we consider the model selection problem in graphical LASSO. Particularly, we compare various model selection criteria via simulations and analyze a real financial data set.

A Study on the Characteristics of Urban Public Transportation Information Services Use (도시 대중교통정보 이용 행동 특성 연구)

  • Joh, Chang-Hyeon;Lee, Back-Jin;Bin, Mi-Young
    • Journal of the Economic Geographical Society of Korea
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    • v.12 no.1
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    • pp.56-66
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    • 2009
  • As the amount of information is rapidly growing, and the ubiquitous urban environments are emerging, the question which information type to provide and which communication media to support is a major challenge for commercial and public travel-information service providers. The current research reports the first findings of analyses of recent data, collected in metropolitan Seoul, about the acquisition of travel information and the communication media used. The study is based on the assumption that information acquisition and choice of communication medium is strongly context-driven. The study applies CHAID analysis to find homogeneous segments in information acquisition and use of communication media. Findings indicate that transport mode and activity are important determinant of information acquisition and choice of media. The type of travel information acquired co-varies strongly with transport mode and activity. In addition, we found evidence of time of day effects. Similarly, the choice of communication medium depends on the type of travel information searched for, transport mode and activity. The results suggest important implications of managerial and policy measures, in particular the dynamic, contextual market segmentation.

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Effects of Information Retrieval and Coffee Shop's Attributes on the Means of Repositioning (정보검색과 커피전문점 선택속성이 재방문 의도에 미치는 영향)

  • Baek, Young Ju;Lee, Min Jung
    • The Journal of the Korea Contents Association
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    • v.20 no.9
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    • pp.549-557
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    • 2020
  • Recently, the number of coffee shops has continued to increase, and information searches have been increasing for consumers who want to visit coffee shops. We wanted to find out the impact on the intention of revisiting a coffee shop by adding information search factors to the existing coffee shop's selection properties and search for the actual selection properties, and summarize the results as follows. The analysis of this study was conducted in two ways, before and after visiting a coffee shop through information search. First, the four factors and optional attributes that are important in information retrieval were the reliability of information (the number of reviews and views by coffee shops, recent postings), physical environment (the proximity of stores, the atmosphere, size, presence of side menus), visuality of information (physical environment, background, design, easy composition), merchantability (the taste of coffee, convenience of parking). In addition, the selection properties for satisfaction after visiting coffee shops through information search were derived from five general characteristics of coffee shops, menu, information consistency, taste of coffee, and convenience of parking, and among them, the consistency of information, taste of coffee, and general characteristics of coffee were found to affect the intention of revisiting again.

Analysis of Factors Influencing Personal Media Creators' Platform Selection : Focusing on YouTube, Twitch and AfreecaTV (1인 미디어 창작자의 플랫폼 선택에 영향을 미치는 요인 연구 : 유튜브, 트위치, 아프리카TV를 중심으로)

  • Bang, Eun-Hye;Kim, Ye-Lim;Na, Hwaseong;Lee, Sang-Woo
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.562-582
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    • 2022
  • Although personal media have become a giant industry, there is a lack of understanding of personal media creators. Therefore, this study aims to clarify factors influencing personal media creators' choice of platform. According to the analysis, there is a significant difference between the factors considered by YouTube, AfreecaTV, and Twitch creators. Moreover, the moderating effect of creators' main genre and broadcasting type were also found to be partially significant. It was found that both creators who share the motive of vividness and communication as their main genre and creators who focus on recording and broadcasting with career development motivation prefer YouTube.