• Smart Media Journal
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• v.13 no.3
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• pp.36-44
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• 2024

Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In order to compare various AI semiconductors, each chip is analyzed in terms of operation unit, speed, power, and energy efficiency. We introduce currently existing optimization methodologies for AI computation. Based on this, future research directions for AI semiconductors are presented in this paper.

• Broadcasting and Media Magazine
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• v.25 no.4
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• pp.46-50
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• 2020

• It's Smart Media
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• v.5 no.1
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• pp.7-10
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• 2016

• Broadcasting and Media Magazine
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• v.26 no.1
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• pp.76-96
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• 2021

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.72-83
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• 2021

The use of the predictive analytics (PA) powered by the artificial intelligence (AI) is more important in the movie sector during the COVID-19 pandemic, because Hollywood witnessed the impact of the 'Netflix Effect' and began to invest in data and AI. Our purpose is to discover a few cases of the AI centered PA in the movie industry value chain based on five objectives of PA: Compete, grow, enforce, improve, and satisfy. Even if movie companies' interest is to predict future success for competing with over-the-tops (OTTs) at a first glance, it is observed, once they start to use the PA with the AI, they try to utilize the enhanced PA platforms for remaining four objectives. As a result, ScriptBook, Vault, Pilot, Cinelytic and Merlin Video (Merlin) are use cases for the objective 'compete.' Movio of Vista Group International and Datorama of Salesforce are use cases for the objective 'grow.' Industrial Light & Magic (ILM) and Geena Davis Institute on Gender in Media (GDI) with Disney are use cases for the objective 'enforce.' Watson, Benjamin, and Greenlight Essential are use cases for the objective 'improve.' Disney Research (DR) with Simon Fraser University and California Institute of Technology is the use case for the objective 'satisfy.'

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.136-138
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• 2022

스포츠 방송/미디어 데이터에서 특정 이벤트 시점을 효율적으로 검출하는 방법은 정보 검색이나 하이라이트, 요약 등을 위해 중요한 기술이다. 이 논문에서는, 야구 중계 방송 데이터에서 투구에 대한 타격 및 포구 이벤트 시점을 강인하게 검출하는 방법으로, 음향 및 영상 정보를 융합하는 방법에 대해 제안한다. 음향 정보에 기반한 이벤트 검출 방법은 계산이 용이하고 정확도가 높은 반면, 영상 정보의 도움 없이는 모호성을 해결하기 힘든 경우가 많이 발생한다. 특히 야구 중계 데이터의 경우, 투수의 투구 시점에 대한 영상 정보를 활용하여 타격 및 포구 이벤트 검출의 정확도를 보다 향상시킬 수 있다. 이 논문에서는 음향 기반의 딥러닝 이벤트 시점 검출 모델과 영상 기반의 보정 방법을 제안하고, 실제 KBO 야구 중계 방송 데이터에 적용한 사례와 실험 결과에 대해 기술한다.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.548-562
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• 2022

This study was conducted to diagnose the issues of AI ethics in global content and to discuss what kind of discourse is needed to strengthen human identity. To this end, the study selected Netflix original content "The Social Dilemma" for analysis and adopted narrative analysis as the research method. The analysis results confirmed that "Social Dilemma" showed the structure of a traditional current affairs documentary and mainly used experts and statistical data to develop the story. It also reinforced core content claims by enumerating domestic and foreign cases such as the 2021 Myanmar massacre and the spread of fake news. In addition, the relationship between the characters clearly revealed the binary opposition between developers and media companies as well as users and advertisers. For the solution to the problem, strong regulations on businesses and the suspension of social media use were reached. However, "The Social Dilemma" merely pointed out the misuse of AI technology and had a narrative that ignored human identity and social relationships. Such results raise the need for creating contents that emphasize the importance of human sociality, relationships, and learning ability in the age of AI.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.374-381
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• 2022

This study analyzes the visual perceptual difference of observers in the artworks created by human artists and artificial intelligence(AI) through eye-tracking. More specifically, the study analyzes the degree of visual attention through a fixation experiment on non-linguistic sources such as the formation and expression of artworks. As a result of this study, the subjects had guessed that one out of four artworks were created by AI (in actuality, 61.1% of the artworks were created by The Next Rembrandt). This demonstrates that most of the subjects hardly recognized the difference between the artwork of human artists and AI. From the comparative analysis of visual perceptual differences found through eye-tracking, more visual attention was found to be demanded for catching details of more stimulating visuals compared to less stimulating visuals. In the gender difference analysis, both of the female and male subjects were likely to stare more intently at the flowers of still-life paintings (Deep Dream & Vincent Van Gogh) while the eyes of a portrait painting (Rembrandt & The Next Rembrandt); this demonstrates no significant differences in gender. Various opinions on AI and art creation from different perspectives arose, therefore, this research is meaningful in a way that it suggests an objective examination through experiments with an artistic perspective.

• Broadcasting and Media Magazine
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• v.28 no.2
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• pp.2-7
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• 2023

본고에서는 서울대학교 정보신호처리연구실, 영문명 ISPL(Intelligent Signal Processing Lab)을 소개하고, 향후 신호처리의 연구 방향을 전망해 본다. ISPL은 1999년 서울대학교 전기공학부에 설치하였고, 지금까지 34명의 박사와 20명의 석사를 배출하였으며, 졸업생들은 현재 삼성전자, LG, 네이버, NCSOFT, SK hynix, 삼성SDS, 한국생산기술연구원, 한국전자기술연구원, KT, SAP, Apple, Meta AI, 한양대, 명지대, 아주대, 숭실대 등으로 진출하여 연구 활동을 하고 있다. 1장에서는 ISPL의 초기부터 현재까지의 연구 분야를 대략 세 단계로 나누어서 소개하고, 2장에서는 딥 러닝과 AI 시대에 신호처리의 역할과 연구 방향을 전망한다.

• Smart Media Journal
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• v.11 no.11
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• pp.40-48
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• 2022

In this paper, an educational kit that can be used in AI education was developed to solve the difficulties of AI education. Through this, object detection and person detection in computer vision using CNN and OpenCV to learn practical-oriented experiences from theory-centered and user image recognition (Your Own) that learns and recognizes specific objects Image Recognition), user object classification (Segmentation) and segmentation (Classification Datasets), IoT hardware control that attacks the learned target, and Jetson Nano GPIO, an AI board, are developed and utilized to develop and utilize textbooks that help effective AI learning made it possible.