• 한국컴퓨터정보학회논문지
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• 제29권11호
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• pp.137-144
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• 2024

본 연구에서는 게임 개발 학습 수요자들을 대상으로 효과적인 생성형 AI 교육 방향을 고안하고자 한다. 과거 인공지능 기술은 게임의 콘텐츠 생성에 활용되었으나, 생성형 AI의 등장과 급속한 발전으로 인해 게임 개발을 위한 도구로 역할이 확장되었다. 이로 인해 게임 개발 전체 과정에 변화를 주고 있다. 그러나 이러한 발전은 학습 수요자들에게 기회뿐만 아니라 불안감을 초래하였다. 이러한 불안감을 해소하고, 학습 수요자들이 전통적인 게임 개발 방식이 아닌 생성형 AI를 활용하여 게임 개발 과정의 일부를 제작하고, 이러한 경험을 통해 생성형 AI에 대한 인식을 변화할 수 있도록 수업을 설계하였다. 교육 이후 설문조사를 통해 생성형 AI에 대한 인식을 조사하고, 생성형 AI를 원활하게 사용하는 데 필요한 능력과 추가 교육 분야에 대한 수요를 수집하였다. 이를 통해 생성형 AI 기술을 효과적으로 교육하는 방법을 제시하며, 앞으로의 생성형 AI 교육 방향성에 대한 시사점을 제공하고자 한다.

• 대한임베디드공학회논문지
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• 제18권5호
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• pp.241-248
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• 2023

GAN (Generative Adversarial Networks) creates highly sophisticated counterfeit products by learning real images or text and inferring commonalities. Therefore, it can be useful in fields that require the creation of large-scale images or graphics. In this paper, we implement GAN-based game character creation AI that can dramatically reduce illustration design work costs by providing expansion and automation of game character image creation. This is very efficient in game development as it allows mass production of various character images at low cost.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.90-95
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• 2023

With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.23-36
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• 2024

Interest in virtual humans continues to increase due to the development of generative AI, extended reality, computer graphics technology, and the spread of a converged metaverse that goes beyond the boundaries between reality and virtuality. Despite the negative public opinion that virtual humans were just temporary form of entertainment event in the early days of their emergence, the reason they are showing continuous growth is due to the unique characteristics of virtual humans and the expansion of diverse usage from technological advancements. The production of video content using virtual humans is becoming vigorously active, but currently there is limitation and no exact process for the technology to apply virtual humans to video content for it to be produced accordingly to the characteristics or situations of virtual humans. In this study, we investigated the characteristics of virtual human production technology methods & processes, and identifying the impact of each production technology on the production environment through examples of virtual human content applied to domestic and international video contents. In conclusion, by proposing an appropriate production method for each content, we hope to develop and assist production practitioners so they can effectively use virtual humans in video content production.