• Title/Summary/Keyword: 생성 AI 콘텐츠

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A Study on the Current Status and Qualitative Development of AI Midjourney 2d Graphic Results (AI미드저니 2d그래픽 결과물의 현황과 질적 적용에 관한 연구)

  • Cho, Hyun Kyung
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.5
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    • pp.803-808
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    • 2024
  • As a service that creates graphic work images with AI, DALL-E2, Midjourney, Stable Diffusion, BING image generator, and Playground AI are widely used. It is that graphic also enables learner-led customized education. With this, it is worth studying detailed design customized learning materials and methods for designing efficient design in future 2D graphic work, and it is necessary to explore the areas of application. The current situation is that it is necessary to develop a design education system that can indicate the lack of AI technology through text security and questions. In this study, a successful proposal for a process that is produced through a process of creating AI design work through proxy work can be presented as a conclusion. Design, advertisement, and visual content companies are already using and adapting, and the trend is to reflect the AI graphic utilization ability and results in the portfolio along with interviews when hiring new employees. In line with this, detailed consideration and research on visual and design production methods for AI convergence between instructors and learners are currently needed. In this paper, proposals and methods for image quality production were considered in the main body and conclusions, and conclusive directions were proposed for five alternatives and methods for future applications.

Learning English Vocabulary Using Synonyms And Antonyms System Design (동의어와 반의어를 활용한 영어 어휘 학습 시스템 설계)

  • Jun-Hyeok Ok;Hong-Jun Jang;Byoungwook Kim
    • Annual Conference of KIPS
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    • 2023.11a
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    • pp.21-22
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    • 2023
  • 영어 공인 시험에서 영어 어휘는 가장 중요한 요소 중 하나이다. 그러나 기존 영어 어휘 학습 시스템은 단순히 어휘 교재의 콘텐츠를 디지털화한 것에 그치고 있다. 영어 어휘 학습에서 동의어에 대한 학습은 언어 능력을 향상시키고 다양한 상황에서 효과적으로 의사소통할 수 있는 능력 향상에 도움이 된다. 본 연구에서는 학습자들이 영어 어휘 학습을 효과적으로 할 수 있도록 동의어 및 반의어를 활용할 수 있는 학습 시스템을 제안한다. 본 시스템은 동의어와 반의어에 대한 정보가 필요한 영어 어휘를 입력으로 받아 생성형 AI에서 동의어 및 반의어에 대한 정보를 생성한 후에 반환하는 기능을 수행한다. 본 시스템은 학습자들이 어휘 평가에서 오답으로 답한 어휘에 대해 동의어 및 반의어에 대한 추가적인 어휘와 예문을 제공하여 영어 어휘 학습의 효율성을 높일 수 있을 것이다.

Future 2nd generation face prediction web service using StyleGAN (StyleGAN을 이용한 미래 2세대 얼굴 예측 웹 서비스)

  • Hwang Kim;Min-Jeong Kim;JI-Hyeon Lee;Jin-Ah Jung;Dong-Uk Kim;Ho-Young Kwak
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.329-330
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    • 2024
  • 최근 생성형 AI에 대한 수요가 상승하고 있으며, MZ세대의 자기애 성향으로 자신의 얼굴을 활용한 미디어 콘텐츠에 대한 호기심이 높아지고 있다. 이에 따라 본 논문에서는 MZ세대의 창의성과 미디어 소비를 고취시키기 위해, StyleGAN 기술을 중심으로 자신과 닮은 2세의 가상 모습을 생성하는 웹 서비스를 설계하고 구현하였다.

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Generation of Stage Tour Contents with Deep Learning Style Transfer (딥러닝 스타일 전이 기반의 무대 탐방 콘텐츠 생성 기법)

  • Kim, Dong-Min;Kim, Hyeon-Sik;Bong, Dae-Hyeon;Choi, Jong-Yun;Jeong, Jin-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.11
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    • pp.1403-1410
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    • 2020
  • Recently, as interest in non-face-to-face experiences and services increases, the demand for web video contents that can be easily consumed using mobile devices such as smartphones or tablets is rapidly increasing. To cope with these requirements, in this paper we propose a technique to efficiently produce video contents that can provide experience of visiting famous places (i.e., stage tour) in animation or movies. To this end, an image dataset was established by collecting images of stage areas using Google Maps and Google Street View APIs. Afterwards, a deep learning-based style transfer method to apply the unique style of animation videos to the collected street view images and generate the video contents from the style-transferred images was presented. Finally, we showed that the proposed method could produce more interesting stage-tour video contents through various experiments.

A Study on the Design Creation of NPC Hanbok in Josun Dynasty Game Using DALL-E API (DALL-E API를 사용한 조선시대 배경의 게임 캐릭터 한복 디자인 생성 연구)

  • Jun-Seok Kyung;Jung-Yi Kim
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.5
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    • pp.673-679
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    • 2024
  • Recently, various contents set in the Josun Dynasty have emerged. However, there is a growing number of hanboks that do not preserve the basic original form of hanbok, such as hanboks that deviate significantly from the form of hanboks. Therefore, in this study, a system was created and implemented in the game to express various colors and patterns of hanbok using the DALL-E API in this game by examining the basic hanbok form of hanbok through literature review. However, despite the fact that the results are inconsistent depending on the quality of the Generative AI service and the limitations of not passing through the historical evidence of traditional hanbok experts, it is meaningful to present a system that uses the creativity of users to create a design that can enhance the aesthetics of traditional hanbok. In future research, we want to investigate users' preferences and develop a system that can create an image that fits them when clicking the interface.

Towards Next Generation Game Development: A Comprehensive Analysis of Game Engines Technologies

  • Soo Kyun Kim;Iqbal Muhamad Ali;Min Woo Ha
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.10
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    • pp.165-173
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    • 2024
  • Game engines are essential tools in game development, speeding up processes and simplifying the integration of various modules like physics, graphics, animations, and AI. This study provides a comprehensive overview of modern game engine technologies, including advanced rendering techniques, graphics APIs, physics simulations, AI integration, audio systems, networking, VR/AR, and development tools. It highlights recent advancements such as real-time ray tracing, physically based rendering, machine learning for content generation and intelligent NPCs, cloud gaming, and novel input methods like brain-computer interfaces. The paper also explores future directions, including enhanced cross-platform support and new technologies that will drive the evolution of game engines. This analysis serves as a valuable resource for developers, researchers, and industry professionals.

A Research on Image Metadata Extraction through YCrCb Color Model Analysis for Media Hyper-personalization Recommendation (미디어 초개인화 추천을 위한 YCrCb 컬러 모델 분석을 통한 영상의 메타데이터 추출에 대한 연구)

  • Park, Hyo-Gyeong;Yong, Sung-Jung;You, Yeon-Hwi;Moon, Il-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.277-280
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    • 2021
  • Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

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SIEM System Performance Enhancement Mechanism Using Active Model Improvement Feedback Technology (능동형 모델 개선 피드백 기술을 활용한 보안관제 시스템 성능 개선 방안)

  • Shin, Youn-Sup;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.896-905
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    • 2021
  • In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

A Study on A Study on the University Education Plan Using ChatGPTfor University Students (ChatGPT를 활용한 대학 교육 방안 연구)

  • Hyun-ju Kim;Jinyoung Lee
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.71-79
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    • 2024
  • ChatGPT, an interactive artificial intelligence (AI) chatbot developed by Open AI in the U.S., gaining popularity with great repercussions around the world. Some academia are concerned that ChatGPT can be used by students for plagiarism, but ChatGPT is also widely used in a positive direction, such as being used to write marketing phrases or website phrases. There is also an opinion that ChatGPT could be a new future for "search," and some analysts say that the focus should be on fostering rather than excessive regulation. This study analyzed consciousness about ChatGPT for college students through a survey of their perception of ChatGPT. And, plagiarism inspection systems were prepared to establish an education support model using ChatGPT and ChatGPT. Based on this, a university education support model using ChatGPT was constructed. The education model using ChatGPT established an education model based on text, digital, and art, and then composed of detailed strategies necessary for the era of the 4th industrial revolution below it. In addition, it was configured to guide students to use ChatGPT within the permitted range by using the ChatGPT detection function provided by the plagiarism inspection system, after the instructor of the class determined the allowable range of content generated by ChatGPT according to the learning goal. By linking and utilizing ChatGPT and the plagiarism inspection system in this way, it is expected to prevent situations in which ChatGPT's excellent ability is abused in education.

An Exploratory Research Trends Analysis in Journal of the Korea Contents Association using Topic Modeling (토픽 모델링을 활용한 한국콘텐츠학회 논문지 연구 동향 탐색)

  • Seok, Hye-Eun;Kim, Soo-Young;Lee, Yeon-Su;Cho, Hyun-Young;Lee, Soo-Kyoung;Kim, Kyoung-Hwa
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.95-106
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    • 2021
  • The purpose of this study is to derive major topics in content R&D and provide directions for academic development by exploring research trends over the past 20 years using topic modeling targeting 9,858 papers published in the Journal of the Korean Contents Association. To secure the reliability and validity of the extracted topics, not only the quantitative evaluation technique but also the qualitative technique were applied step-by-step and repeated until a corpus of the level agreed upon by the researchers was generated, and detailed analysis procedures were presented accordingly. As a result of the analysis, 8 core topics were extracted. This shows that the Korean Contents Association is publishing convergence and complex research papers in various fields without limiting to a specific academic field. Also, before 2012, the proportion of topics in the field of engineering and technology appeared relatively high, while after 2012, the proportion of topics in the field of social sciences appeared relatively high. Specifically, the topic of 'social welfare' showed a fourfold increase in the second half compared to the first half. Through topic-specific trend analysis, we focused on the turning point in time at which the inflection point of the trend line appeared, explored the external variables that affected the research trend of the topic, and identified the relationship between the topic and the external variable. It is hoped that the results of this study can provide implications for active discussions in domestic content-related R&D and industrial fields.