• Title/Summary/Keyword: Content Generation Model

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A Study of an AI-Based Content Source Data Generation Model using Folk Paintings and Genre Paintings (민화와 풍속화를 이용한 AI 기반의 콘텐츠 원천 데이터 생성 모델의 연구)

  • Yang, Seokhwan;Lee, Young-Suk
    • Journal of Korea Multimedia Society
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    • v.24 no.5
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    • pp.736-743
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    • 2021
  • Due to COVID-19, the non-face-to-face content market is growing rapidly. However, most of the non-face-to-face content such as webtoons and web novels are produced based on the traditional culture of other countries, not Korean traditional culture. The biggest cause of this situation is the lack of reference materials for creating based on Korean traditional culture. Therefore, the need for materials on traditional Korean culture that can be used for content creation is emerging. In this paper, we propose a generation model of source data based on traditional folk paintings through the fusion of traditional Korean folk paintings and AI technology. The proposed model secures basic data based on folk tales, analyzes the style and characteristics of folk tales, and converts historical backgrounds and various stories related to folk tales into data. In addition, using the built data, various new stories are created based on AI technology. The proposed model is highly utilized in that it provides a foundation for new creation based on Korean traditional folk painting and AI technology.

Verification of the Validity of Moisture Transfer Model for Prediction of Indoor Moisture Generation Rate (실내 수증기 발생량 예측을 위한 습기 전달 모델의 검증에 관한 연구)

  • Lee, Dong-Kweon;Kim, Eui-Jong;Choi, Won-Ki;Suh, Seung-Jik
    • Journal of the Korean Solar Energy Society
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    • v.26 no.1
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    • pp.41-47
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    • 2006
  • Moisture in a building is one of the most important variables influencing building performance, human health, and comfort of indoor environment. However, there are still lacks in the knowledge of understanding the moisture problem well and controlling moisture. Accordingly, in order to provide the fundamental data to control moisture contents in the indoor air, this study was to predict moisture contents transferred through building envelopes and indoor moisture generation rate. Moisture transfer model was made by physical relations in each node, and the indoor moisture generation rate was gained by comparing the model with experimental analyses. From the study, we found out that moisture generation rate was critical and day-periodic, so that we predicted the indoor moisture content by substituting the constant value gained from the average in a day for the moisture generation rate.

Method and Case Study of Decision Tree for Content Design Education (콘텐츠 디자인교육을 위한 의사 결정 트리 활용 방법과 사례연구)

  • Kim, Sungkon
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.4
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    • pp.283-288
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    • 2019
  • In order to overcome the students' lack of information and experience, we developed a content planning tree that utilizes a decision tree. The content planning tree consists of a tree trunk creation step in which students select a theme and a story to develop, a parent branch generation step for selecting a category that can be developed based on the story, a child branch generation step for selecting the interesting "effect" method of producing the content effectively, a leaf generation step for selecting a multimedia expression 'element' to be visualized. The educational model was applied to game planning design and information visualization lectures, and provides examples of the categories, effects, and elements used in each lecture. The model was used for 145 team projects and the efficiency was confirmed by a step-by-step learning process.

Real-Time 2D-to-3D Conversion for 3DTV using Time-Coherent Depth-Map Generation Method

  • Nam, Seung-Woo;Kim, Hye-Sun;Ban, Yun-Ji;Chien, Sung-Il
    • International Journal of Contents
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    • v.10 no.3
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    • pp.9-16
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    • 2014
  • Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

Generating Sponsored Blog Texts through Fine-Tuning of Korean LLMs (한국어 언어모델 파인튜닝을 통한 협찬 블로그 텍스트 생성)

  • Bo Kyeong Kim;Jae Yeon Byun;Kyung-Ae Cha
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.3
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    • pp.1-12
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    • 2024
  • In this paper, we fine-tuned KoAlpaca, a large-scale Korean language model, and implemented a blog text generation system utilizing it. Blogs on social media platforms are widely used as a marketing tool for businesses. We constructed training data of positive reviews through emotion analysis and refinement of collected sponsored blog texts and applied QLoRA for the lightweight training of KoAlpaca. QLoRA is a fine-tuning approach that significantly reduces the memory usage required for training, with experiments in an environment with a parameter size of 12.8B showing up to a 58.8% decrease in memory usage compared to LoRA. To evaluate the generative performance of the fine-tuned model, texts generated from 100 inputs not included in the training data produced on average more than twice the number of words compared to the pre-trained model, with texts of positive sentiment also appearing more than twice as often. In a survey conducted for qualitative evaluation of generative performance, responses indicated that the fine-tuned model's generated outputs were more relevant to the given topics on average 77.5% of the time. This demonstrates that the positive review generation language model for sponsored content in this paper can enhance the efficiency of time management for content creation and ensure consistent marketing effects. However, to reduce the generation of content that deviates from the category of positive reviews due to elements of the pre-trained model, we plan to proceed with fine-tuning using the augmentation of training data.

Exploratory Study on Factors Affecting Influencers' YouTube Channel Operation and Revenue Generation Based on the Grounded Theory Approach (근거이론 접근법을 이용한 인플루언서의 유튜브 채널 운영과 수익 창출에 미치는 영향요인에 관한 탐색 연구)

  • Kim, Young Lag;Park, Sang Hyeok;Cho, Jae Hee;Park, Jeong Sun
    • The Journal of Information Systems
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    • v.30 no.4
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    • pp.173-202
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    • 2021
  • Purpose This study explored overall phenomena in context such as YouTube channel operation, strategy, and profit generation through interviews with two research participants who started their own businesses and are recognized as influencer on YouTube and analysis of viewer responses to uploaded contents. With the explosive growth of YouTube content provision and use, previous studies on YouTube are only being conducted individually on YouTube's content, influence, and content providers, so it is need to explore YouTube channel operations and the effect of revenue generation in context from an integrated perspective. Therefore, the purpose of this study is to present an integrated model that provides a specific process by contextually linking the factors and results influencing YouTube channel operation and revenue generation phenomena to individuals and companies who are trying to operate YouTube channels for the first time. Design/methodology/approach This study systematized and structured the overall phenomena in context such as YouTube channel operation, communication strategy, effect on revenue generation, and YouTube channel operation results by selecting interview subjects and collecting data through interviews, and analyzing viewer reactions (likes, comments, etc.). Due to the lack of previous studies exploring integrated phenomena, research analysis used Strauss & Corbin (1998)'s grounded theory approach, which presented inductive research methods to discover new theories by structuring concepts and categories based on detailed observations and information provided by interviewees. Findings The academic implication of this study is that while previous studies are conducted as individual studies on YouTube's content, influence, and content providers in the current situation where YouTube content provision and use are exploding, it integrally explores and presents an integrated model throughout the process. In addition, taking into account the lack of previous studies, it can be found in the aspect of using the grounded theory approach, an inductive theory approach that establishes a new theory. The practical implications can be found in that it presented practical directions to beginners who want to start operating YouTube channels by identifying operational preparations, communication strategies with viewers, and response management strategies.

Biological Infectious Watermarking Model for Video Copyright Protection

  • Jang, Bong-Joo;Lee, Suk-Hwan;Lim, SangHun;Kwon, Ki-Ryong
    • Journal of Information Processing Systems
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    • v.11 no.2
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    • pp.280-294
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    • 2015
  • This paper presents the infectious watermarking model (IWM) for the protection of video contents that are based on biological virus modeling by the infectious route and procedure. Our infectious watermarking is designed as a new paradigm protection for video contents, regarding the hidden watermark for video protection as an infectious virus, video content as host, and codec as contagion medium. We used pathogen, mutant, and contagion as the infectious watermark and defined the techniques of infectious watermark generation and authentication, kernel-based infectious watermarking, and content-based infectious watermarking. We experimented with our watermarking model by using existing watermarking methods as kernel-based infectious watermarking and content-based infectious watermarking medium, and verified the practical applications of our model based on these experiments.

2D Game Image Color Synthesis System Using Convolutional Neural Network (컨볼루션 인공신경망을 이용한 2차원 게임 이미지 색상 합성 시스템)

  • Hong, Seung Jin;Kang, Shin Jin;Cho, Sung Hyun
    • Journal of Korea Game Society
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    • v.18 no.2
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    • pp.89-98
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    • 2018
  • The recent Neural Network technique has shown good performance in content generation such as image generation in addition to the conventional classification problem and clustering problem solving. In this study, we propose an image generation method using artificial neural network as a next generation content creation technique. The proposed artificial neural network model receives two images and combines them into a new image by taking color from one image and shape from the other image. This model is made up of Convolutional Neural Network, which has two encoders for extracting color and shape from images, and a decoder for taking all the values of each encoder and generating a combination image. The result of this work can be applied to various 2D image generation and modification works in game development process at low cost.

Adsorption Characteristics of Short Grain Rough Rice (단립종 벼의 수분흡습특성)

  • 김종순;고학균;송대빈
    • Journal of Biosystems Engineering
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    • v.23 no.5
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    • pp.465-472
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    • 1998
  • In this study short gain rough rice(Chu-cheong) with initial moisture content of around 12%(w.b.) was exposed to 3 levels of relative humidity(70, 80 and 90%) and 3 levels of temperature(20, 25 and 3$0^{\circ}C$) of the air, in order to evaluate the adsorption characteristics of rough rice and the rate of cracked kernels which will serve as the basic data when developing the quality adjusting equipment. The result showed that the moisture content of rough rice increased rapidly during the early stages of moisture adsorption like other grains, and at least 70% of the adsorption occurred within the first 24 hours of exposure to the humid environment. Adsorption rate was more related to relative humidity than the temperature of air stream, and the higher the relative humidity, the higher the adsorption rate. And the Page's equation predicted best the adsorption process of this study. Experimental results for the crack generation during the adsorption process showed that the higher the relative humidity the more the cracked kernels, and that the temperature had little effect. An empirical equation was developed to predict the crack ratio for the conditions of this study, and Nishiyama model predicted better the crack generation than Hoerl model.

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Software Design Framework for Content Creation (콘텐츠 제작을 위한 소프트웨어 디자인 프레임워크)

  • Oh, Jung-Min;Moon, Nammee
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.11
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    • pp.815-822
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    • 2013
  • Nowadays, the various kind of software packages that support content creation consumed in touch-type terminals as an application have come into the market. These softwares have a different style of user task compare to existing user task. The reason why difference style has been appeared for now is because interaction timing has a important role of both content creation and consumption. For this reason, in this paper, we propose a software UI design framework for content creation using MB-UID and UCD model based on task modeling. The proposed framework is made up of five steps: business rule model, creation role model, creation flow model, creation action model, presentation model. Through this framework, we handle the interaction between a content creator and software user interface at the content creation phase. At the same time, we consider a possible interaction type which can occur by consumers at the consumption phase in advance.