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      인공지능 기반 문화예술 콘텐츠 창작 기술 분석 및 도구 설계

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      https://www.riss.kr/link?id=A107894094

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      다국어 초록 (Multilingual Abstract)

      This paper proposes an arts and culture content creation tool powered by artificial intelligence. With the recent advances in technologies including artificial intelligence, there are active research activities on creating art and culture contents. However, it is still difficult and cumbersome for those who are not familiar with programming and artificial intelligence. In order to deal with the content creation with new technologies, we analyze related creation tools, services and technologies that process with raw visual and audio data, generate new media contents and visualize intermediate results. We then extract key requirements for a future creation tool for creators who are not familiar with programming and artificial intelligence. We finally introduce an intuitive and integrated content creation tool for end-users. We hope that this tool will allow creators to intuitively and creatively generate new media arts and culture contents based on not only understanding given data but also adopting new technologies.
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      This paper proposes an arts and culture content creation tool powered by artificial intelligence. With the recent advances in technologies including artificial intelligence, there are active research activities on creating art and culture contents. Ho...

      This paper proposes an arts and culture content creation tool powered by artificial intelligence. With the recent advances in technologies including artificial intelligence, there are active research activities on creating art and culture contents. However, it is still difficult and cumbersome for those who are not familiar with programming and artificial intelligence. In order to deal with the content creation with new technologies, we analyze related creation tools, services and technologies that process with raw visual and audio data, generate new media contents and visualize intermediate results. We then extract key requirements for a future creation tool for creators who are not familiar with programming and artificial intelligence. We finally introduce an intuitive and integrated content creation tool for end-users. We hope that this tool will allow creators to intuitively and creatively generate new media arts and culture contents based on not only understanding given data but also adopting new technologies.

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      참고문헌 (Reference)

      1 "tSNE Java Script demo"

      2 A. Ramesh, "Zero-Shot Text-to-Image Generation"

      3 J. Redmon, "YOLOv3: An Incremental Improvement"

      4 J. Redmon, "YOLO9000: Better, Faster, Stronger" 6517-6525, 2017

      5 A. S. Cowen, "What music makes us feel: At least 13 dimensions organize subjective experiences associated with music across different cultures" 117 (117): 1924-1934, 2020

      6 L. Maaten, "Visualizing High-Dimensional Data Using t-SNE" 9 : 2579-2605, 2008

      7 "The Next Rembrandt"

      8 "Teachable Machine"

      9 "T-SNE visualization"

      10 C. Weng, "Photo Wake-Up: 3D Character Animation From a Single Photo"

      1 "tSNE Java Script demo"

      2 A. Ramesh, "Zero-Shot Text-to-Image Generation"

      3 J. Redmon, "YOLOv3: An Incremental Improvement"

      4 J. Redmon, "YOLO9000: Better, Faster, Stronger" 6517-6525, 2017

      5 A. S. Cowen, "What music makes us feel: At least 13 dimensions organize subjective experiences associated with music across different cultures" 117 (117): 1924-1934, 2020

      6 L. Maaten, "Visualizing High-Dimensional Data Using t-SNE" 9 : 2579-2605, 2008

      7 "The Next Rembrandt"

      8 "Teachable Machine"

      9 "T-SNE visualization"

      10 C. Weng, "Photo Wake-Up: 3D Character Animation From a Single Photo"

      11 Z. Cao, "OpenPose:Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields" 43 (43): 172-186, 2021

      12 "Music visualization"

      13 H. Dong, "MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment" 2018

      14 Z. Wolkowicz, "Midivis: Visualizing Music Structure via Similarity Matrices" 53-56, 2009

      15 "Magenta"

      16 D. M. Blei, "Latent Dirichlet Allocation" 3 : 993-1022, 2003

      17 C. Sievert, "LDAvis: A method for visualizing and interpreting topics" 63-70, 2014

      18 T. Ishibashi, "Investigating audio data visualization for interactive sound recognition" Association for Computing Machinery 67-77,

      19 A. Krizhevsky, "ImageNet classification with deep convolutional neural networks" Curran Associates Inc 1 : 1097-1105,

      20 P. Isola, "Image-to-Image Translation with Conditional Adversarial Networks" 5967-5976, 2017

      21 P. Isola, "Image-to-Image Translation with Conditional Adversarial Networks" 5967-5976, 2017

      22 L. A. Gatys, "Image Style Transfer Using Convolutional Neural Networks" 2414-2423, 2016

      23 M. Wattenberg, "How to Use t-SNE Effectively" 2016

      24 "Google Arts & Culture"

      25 "Deep dream generator"

      26 K. He, "Deep Residual Learning for Image Recognition" 770-778, 2016

      27 S. Minaee, "Deep Learning-based Text Classification: A Comprehensive Review" 54 (54): 2021

      28 J. P. Briot, "Computational Synthesis and Creative Systems" Springer 2017

      29 S. Hershey, "CNN architectures for large-scale audio classification" 131-135, 2017

      30 "Autodraw"

      31 Z. Kastrati, "A Deep Learning Sentiment Analyser for Social Media Comments in Low-Resource Languages" 10 (10): 1133

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      연관논문

      연구자 네트워크맵

      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2026 평가예정 재인증평가 신청대상 (재인증)
      2020-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2017-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2016-01-15 학회명변경 한글명 : 한국방송공학회 -> 한국방송∙미디어공학회
      영문명 : The Korean Society Of Broadcast Engineers -> The Korean Institute of Broadcast and Media Engineers
      KCI등재
      2013-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2006-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2004-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.38 0.38 0.34
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.32 0.27 0.526 0.14
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