• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.867-871
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• 2022

Amid the recent rapid trend change, the change in design has a great impact on the sales of fashion companies, so it is inevitable to be careful in choosing new designs. With the recent development of the artificial intelligence field, various machine learning is being used a lot in the fashion market to increase consumers' preferences. To contribute to increasing reliability in the development of new products by quantifying abstract concepts such as preferences, we generate new images that do not exist through three adversarial generative neural networks (GANs) and numerically compare abstract concepts of preferences using pre-trained convolution neural networks (CNNs). Deep convolutional generative adversarial networks (DCGAN), Progressive growing adversarial networks (PGGAN), and Dual Discriminator generative adversarial networks (DANs), which were trained to produce comparative, high-level, and high-level images. The degree of similarity measured was considered as a preference, and the experimental results showed that D2GAN showed a relatively high similarity compared to DCGAN and PGGAN.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.357-364
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• 2023

Due to the rapid advancement of AI technology, generative artificial intelligence platforms are experiencing innovative applications in various fields. In this paper, it examines research cases involving the utilization of AI in education, explore instances where generative AI platforms are applied in the realm of creative endeavors, and discuss the direction of utilizing generative AI in educational contexts. In the field of computer graphics, this study introduced generative AI platforms that are applicable for image creation, editing, and video editing. It also proposed platforms that can be utilized in the video editing production process. These generative AI platforms not only offer advantages in terms of efficiency, by reducing the efforts of creators and saving time in the production process, but they also present positive aspects in enhancing individual capabilities. It is advocated that their swift integration into education is necessary, considering these benefits. This study aims to provide direction for the expansion of creative education utilizing generative AI platforms.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.181-192
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• 2024

With the introduction of generative artificial intelligence(AI) tools such as OpenAI's Sora into the global film industry, including Hollywood, there has been a simultaneous emergence of innovations in film production as well as various crises. These changes are spreading throughout the entire film production process, including scriptwriting, casting, editing, and acting. This study analyzes the impact of AI on the film industry, particularly Hollywood, and explores how this technology might bring about changes in Korean cinema. AI technologies applied in the film industry offer benefits such as reducing production time and costs. However, they also pose threats to many filmmakers and actors who rely on the traditional production methods, leading to ethical and legal issues. In Hollywood blockbuster films, AI technology is used to create realistic visual effects, analyze scripts, and suggest optimal shooting angles. While these applications improve the qualitative level of films, they also reduce the human resources required in traditional film production processes. The impact on the Korean film industry is also noteworthy. Some Korean film production companies are leveraging AI to create films in a more creative and efficient manner. Efforts are being made to analyze audience data using AI and develop storylines that appeal to a larger audience. However, these technological changes are controversial among many Korean filmmakers who prefer traditional production methods. This study provides an in-depth discussion on whether the adoption of AI in the film industry can bring about positive innovation or inevitably lead to crises. It analyzes how AI technology is transforming traditional roles in the film industry and what new opportunities and challenges this change generates within the industry. Additionally. This study highlights the differences in technology adoption between Hollywood and Korean film industry and explores how each industry is embracing these technological changes.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.195-204
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• 2023

In this study, prompt engineering that improves prompts was explored to improve the performance of teaching and learning materials recommendations using generative artificial intelligence such as GPT and Stable Diffusion. Picture materials were used as the types of teaching and learning materials. To explore the impact of the prompt composition, a Zero-Shot prompt, a prompt containing learning target grade information, a prompt containing learning goals, and a prompt containing both learning target grades and learning goals were designed to collect responses. The collected responses were embedded using Sentence Transformers, dimensionalized to t-SNE, and visualized, and then the relationship between prompts and responses was explored. In addition, each response was clustered using the k-means clustering algorithm, then the adjacent value of the widest cluster was selected as a representative value, imaged using Stable Diffusion, and evaluated by 30 elementary school teachers according to the criteria for evaluating teaching and learning materials. Thirty teachers judged that three of the four picture materials recommended were of educational value, and two of them could be used for actual classes. The prompt that recommended the most valuable picture material appeared as a prompt containing both the target grade and the learning goal.

• Information Systems Review
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• v.25 no.2
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• pp.125-144
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• 2023

Generative Artificial Intelligence (AI) technology is gaining global attention as it can automatically generate sentences, images, and voices that humans previously generated. In particular, ChatGPT, a representative generative AI service, shows proactivity and accuracy differentiated from existing chatbot services, and the number of users is rapidly increasing in a short period of time. Despite this growing interest in generative AI services, most preceding studies are still in their infancy. Therefore, this study utilized LDA topic modeling and keyword network diagrams to derive success factors for generative AI services and to propose successful business strategies based on them. In addition, using ChatGPT, a new research methodology that complements the existing text-mining method, was presented. This study overcomes the limitations of previous research that relied on qualitative methods and makes academic and practical contributions to the future development of generative AI services.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.613-625
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• 2024

This study analyzed the convergence case of AI painting and NFT art, art content created based on digital technology, an innovative technology of the 4th industrial technology, and explored its characteristics. Digital technology that innovates the paradigm of life in the 21st century is being used in creative art, and AI painting and NFT art that use it as an expression tool are changing the way they perceive and accept art. AI painting using big data and artificial intelligence technology is evolving into interactive daily art, and NFT art using blockchain and NFT technology is becoming the art of the metaverse with economic and cultural values. Therefore, this study attempted to explore various aspects and values of these digital convergence arts. For the study, representative examples of AI painting and NFT art were classified into cognitive creative AI painting and language generative AI, art economic NFTs, and art and cultural NFTs, and their characteristics, contents, and meanings were analyzed. It is hoped that the results of this study will contribute to the development of AI painting and NFT art, which are digital convergence arts.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.97-98
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• 2024

4차 산업 혁명의 시작으로 인공지능이 빠르게 발달함에 따라 현재 생성형 인공지능이 주목받고 있다. 이에 따라 딥보이스 기술과 딥페이크 기술을 활용하여 다양한 범죄가 발생하고 있어 관련 사례와 이를 해결하기 위해 진행 중인 연구에 대해서 조사하였다. 딥보이스와 딥페이크를 탐지하는 연구는 지속되고 있지만 관련 기술이 상용화되어 있지 않아 범죄를 예방하기에는 부족한 실정이다. 범죄에 악용되는 속도가 빨라지고 있는 만큼 더 많은 연구가 신속하게 이루어져야 한다.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.403-406
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• 2024

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.81-86
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• 2024

Advancements in generative AI are reshaping graphic and 3D content design landscapes, where AI not only enriches graphic design but extends its reach to 3D content creation. Though 3D texture mapping through AI is advancing, AI-generated 3D modeling technology in this realm remains nascent. This paper presents AI 2D image-driven 3D modeling techniques, assessing their viability in 3D content design by scrutinizing various algorithms. Initially, four OBJ model-exporting AI algorithms are screened, and two are further evaluated. Results indicate that while AI-generated 3D models may not be directly usable, they effectively capture reference object structures, offering substantial time savings and enhanced design efficiency through manual refinements. This endeavor pioneers new avenues for 3D content creators, anticipating a dynamic fusion of AI and 3D design.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.351-358
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• 2022

Recently, Generative Adversarial Networks (GAN) and Variational AutoEncoders (VAE) have been applied to voice conversion that can make use of non-parallel training data. Especially, Conditional Cycle-Consistent Generative Adversarial Networks (CC-GAN) and Cycle-Consistent Variational AutoEncoders (CycleVAE) show promising results in many-to-many voice conversion among multiple speakers. However, the number of speakers has been relatively small in the conventional voice conversion studies using the CC-GANs and the CycleVAEs. In this paper, we extend the number of speakers to 100, and analyze the performances of the many-to-many voice conversion methods experimentally. It has been found through the experiments that the CC-GAN shows 4.5 % less Mel-Cepstral Distortion (MCD) for a small number of speakers, whereas the CycleVAE shows 12.7 % less MCD in a limited training time for a large number of speakers.