• Title/Summary/Keyword: media intelligence

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Analysis and Design of Arts and Culture Content Creation Tool powered by Artificial Intelligence (인공지능 기반 문화예술 콘텐츠 창작 기술 분석 및 도구 설계)

  • Shin, Choonsung;Jeong, Hieyong
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.489-499
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    • 2021
  • This paper proposes an arts and culture content creation tool powered by artificial intelligence. With the recent advances in technologies including artificial intelligence, there are active research activities on creating art and culture contents. However, it is still difficult and cumbersome for those who are not familiar with programming and artificial intelligence. In order to deal with the content creation with new technologies, we analyze related creation tools, services and technologies that process with raw visual and audio data, generate new media contents and visualize intermediate results. We then extract key requirements for a future creation tool for creators who are not familiar with programming and artificial intelligence. We finally introduce an intuitive and integrated content creation tool for end-users. We hope that this tool will allow creators to intuitively and creatively generate new media arts and culture contents based on not only understanding given data but also adopting new technologies.

ETRI AI Strategy #3: Leading Future Technologies of Network, Media, and Content (ETRI AI 실행전략 3: 네트워크 및 미디어·콘텐츠 미래기술 선도)

  • Kim, S.M.;Yeon, S.J.
    • Electronics and Telecommunications Trends
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    • v.35 no.7
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    • pp.23-35
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    • 2020
  • In this paper, we introduce ETRI AI Strategy #3, "Leading Future Technologies of Network, Media, and Content." Its first goal is "to innovate AI service technology to overcome the current limitations of AI technologies." Artificial intelligence (AI) services, such as self-driving cars and robots, are combinations of computing, network, AI algorithms, and other technologies. To develop AI services, we need to develop different types of network, media coding, and content creation technologies. Moreover, AI technologies are adopted in ICT technologies. Self-planning and self-managing networks and automatic content creation technologies using AI are being developed. This paper introduces the two directions of ETRI's ICT technology development plan for AI: ICT for AI and ICT by AI. The area of ICT for AI has only recently begun to develop. ETRI, the ICT leader, hopes to have opportunities for leadership in the second wave of AI services.

Development and Validation of a Digital Literacy Scale in the Artificial Intelligence Era for College Students

  • Ha Sung Hwang;Liu Cun Zhu;Qin Cui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2241-2258
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    • 2023
  • This study developed digital literacy instruments and tested their effectiveness on college students' perceptions of AI technologies. In creating a new digital literacy test tool, we reviewed the concept and scale of digital literacy based on previous studies that identified the characteristics and measurement of AI literacy. We developed 23 preliminary questions for our research instrument and used a quantitative approach to survey 318 undergraduates. After conducting exploratory and confirmatory factor analysis, we found that digital literacy in the age of AI had four ability sub-factors: critical understanding, artificial intelligence social impact recognition, artificial intelligence technology utilization, and ethical behavior. Then we tested the sub-factors' predictive powers on the perception of AI's usefulness and ease of use. The regression result shows that the most common powerful predictor of the usefulness and ease of use of AI technology was the ability to use AI technology. This finding implies that for college students, the ability to use various tools based on AI technology is an essential competency in the AI era.

A Study on the Method of Creating Realistic Content in Audience-participating Performances using Artificial Intelligence Sentiment Analysis Technology (인공지능 감정분석 기술을 이용한 관객 참여형 공연에서의 실감형 콘텐츠 생성 방식에 관한 연구)

  • Kim, Jihee;Oh, Jinhee;Kim, Myeungjin;Lim, Yangkyu
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.533-542
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    • 2021
  • In this study, a process of re-creating Jindo Buk Chum, one of the traditional Korean arts, into digital art using various artificial intelligence technologies was proposed. The audience's emotional data, quantified through artificial intelligence language analysis technology, intervenes in various object forms in the projection mapping performance and affects the big story without changing it. If most interactive arts express communication between the performer and the video, this performance becomes a new type of responsive performance that allows the audience to directly communicate with the work, centering on artificial intelligence emotion analysis technology. This starts with 'Chuimsae', a performance that is common only in Korean traditional art, where the audience directly or indirectly intervenes and influences the performance. Based on the emotional information contained in the performer's 'prologue', it is combined with the audience's emotional information and converted into the form of images and particles used in the performance to indirectly participate and change the performance.

Link Stability aware Reinforcement Learning based Network Path Planning

  • Quach, Hong-Nam;Jo, Hyeonjun;Yeom, Sungwoong;Kim, Kyungbaek
    • Smart Media Journal
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    • v.11 no.5
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    • pp.82-90
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    • 2022
  • Along with the growing popularity of 5G technology, providing flexible and personalized network services suitable for requirements of customers has also become a lucrative venture and business key for network service providers. Therefore, dynamic network provisioning is needed to help network service providers. Moreover, increasing user demand for network services meets specific requirements of users, including location, usage duration, and QoS. In this paper, a routing algorithm, which makes routing decisions using Reinforcement Learning (RL) based on the information about link stability, is proposed and called Link Stability aware Reinforcement Learning (LSRL) routing. To evaluate this algorithm, several mininet-based experiments with various network settings were conducted. As a result, it was observed that the proposed method accepts more requests through the evaluation than the past link annotated shorted path algorithm and it was demonstrated that the proposed approach is an appealing solution for dynamic network provisioning routing.

Optimization of Action Recognition based on Slowfast Deep Learning Model using RGB Video Data (RGB 비디오 데이터를 이용한 Slowfast 모델 기반 이상 행동 인식 최적화)

  • Jeong, Jae-Hyeok;Kim, Min-Suk
    • Journal of Korea Multimedia Society
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    • v.25 no.8
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    • pp.1049-1058
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    • 2022
  • HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

A TabNet - Based System for Water Quality Prediction in Aquaculture

  • Nguyen, Trong–Nghia;Kim, Soo Hyung;Do, Nhu-Tai;Hong, Thai-Thi Ngoc;Yang, Hyung Jeong;Lee, Guee Sang
    • Smart Media Journal
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    • v.11 no.2
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    • pp.39-52
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    • 2022
  • In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

A study on a model of intercultural learning contents and methods

  • Jong Youl Hong
    • Smart Media Journal
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    • v.13 no.4
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    • pp.104-113
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    • 2024
  • This study is a model study on the contents and methods of intercultural learning. Starting with a discussion of the intercultural learning model construct, it presents key contents important for intercultural learning and learning methods that can increase the effectiveness of intercultural learning. Also, we actually conducted the above learning program at the learning site and discussed the observations and results. It was a case study that allowed us to test the effectiveness of cultural intelligence theory, the latest theory that can improve intercultural competency. In addition, in order for the cultural intelligence theory to be effective in the learning process, it was found that the PBL method, which allows learners to solve problems on their own, rather than cramming education, is useful. Additionally, it was found that the ARCS model was also very effective in motivating and maintaining learners' continuous motivation. At this time, the instructor was also able to see that the effect increases when the role of catalyst becomes the main one.

Design and Utilization of Connected Data Architecture-based AI Service of Mass Distributed Abyss Storage (대용량 분산 Abyss 스토리지의 CDA (Connected Data Architecture) 기반 AI 서비스의 설계 및 활용)

  • Cha, ByungRae;Park, Sun;Seo, JaeHyun;Kim, JongWon;Shin, Byeong-Chun
    • Smart Media Journal
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    • v.10 no.1
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    • pp.99-107
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    • 2021
  • In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

Object Tracking Method Based on Local Moments

  • Takamatsu, R.;Kawarada, H.;Sato, M.
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1997.06a
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    • pp.113-118
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    • 1997
  • This paper proposes a object tracking method based on the local moments, or moment based on the local moments, or moment of some restricted area, in which the idea of the viewpoint and the visual filed corresponding to the local area of an image is introduced. Using local moment with the optimally controlled viewpoint and visual field, the target position and its breadth are estimated robustly. By two experiments, the validity of the proposed method is shown.

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