• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.87-99
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• 2024

This study aims to identify the competencies required for webtoon artists to survive in the future era of AI commercialization. It explores the current and future use of AI in webtoons, and predicts the role of artists in the future webtoon industry. The study finds that AI will replace human workers in some areas, but human empathy-related fields can be sustained. Artist roles like story projectors, Visual directors, and AI editors were identified as potential models for the changing role of artists. To address terminology ambiguity, a three-step AI categorization mechanical type AI, humanoid type AI, and transcendent type AI was proposed for a more realistic separation of AI capabilities. The researcher suggested these findings as guidelines for developing skills in emerging artists or re-skilling existing ones, emphasizing collaboration with AI for mutual growth rather than a negative acceptance of new technology.

• Journal of Platform Technology
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• v.11 no.2
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• pp.3-14
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• 2023

This paper proposes a big data sentiment analysis method and deep learning implementation method to provide a webtoon comment analysis web page for convenient comment confirmation and feedback of webtoon writers for the development of the cartoon industry in the video animation field. In order to solve the difficulty of automatic analysis due to the nature of Internet comments and provide various sentiment analysis information, LSTM(Long Short-Term Memory) algorithm, ranking algorithm, and word2vec algorithm are applied in parallel, and actual popular works are used to verify the validity. If the analysis method of this paper is used, it is easy to expand to other domestic and overseas platforms, and it is expected that it can be used in various video animation content fields, not limited to the webtoon field

• Smart Media Journal
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• v.12 no.7
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• pp.76-83
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• 2023

This study proposes a method to assist webtoon artists in the process of webtoon creation by utilizing a pretrained Text-to-Image model to generate webtoon images from text. The proposed approach involves fine-tuning a pretrained Stable Diffusion model using a webtoon dataset transformed into the desired webtoon style. The fine-tuning process, using LoRA technique, completes in a quick training time of approximately 4.5 hours with 30,000 steps. The generated images exhibit the representation of shapes and backgrounds based on the input text, resulting in the creation of webtoon-like images. Furthermore, the quantitative evaluation using the Inception score shows that the proposed method outperforms DCGAN-based Text-to-Image models. If webtoon artists adopt the proposed Text-to-Image model for webtoon creation, it is expected to significantly reduce the time required for the creative process.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.521-524
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• 2023

본 연구에서는 AI 인공지능을 활용한 통일신라 석탑 '경주 불국사 삼층석탑' 복원을 위해 석탑 3D모델링 과정에 대한 연구를 수행하였다. 산성비로 부식되어 갈라진 더 이상 원본의 형태를 알아 볼 수 없는 현재 통일신라 석탑 형태를 3D모델링 작업을 통하여 AI로 하여금 원활한 교육이 실시 되도록 하는 것을 목표로한다. 본래 제작 되어있는 3D 모델링은 많은 버텍스와 페이스로 학습 데이터가 많아 실제 활용하기에 어려움을 가지고 있다. 때문에 적은 양의 버텍스와 페이스로 새로운 3D 모델링 제작에 대한 필요성에 대해 확인하였다. 본 연구는 그에 필요한 석탑 모델링 과정에 대해 서술한다. 이를 위해 본 논문은 석탑에 대한 구조를 살피고 모델링에 활용된 프로그램의 장단점과 분석을 도출하였다. 본 연구를 통해 석탑 복원에 필요한 3D모델링 프로그램 활용의 전망과 더불어 인공지능 AI의 한계점을 3D 모델링의 정확도와 세밀함을 통하여 타파하고자 하였다.