• Title/Summary/Keyword: AI technology

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A Study on the Militarization of Artificial Intelligence Technology in North Korea and the Development Direction of Corresponding Weapon System in South Korea (북한 인공지능 기술의 군사화와 우리 군의 대응 무기체계 발전방향 연구)

  • Kim, Min-Hyuk
    • Journal of Information Technology Services
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    • v.20 no.1
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    • pp.29-40
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    • 2021
  • North Korea's science and technology policies are being pursued under strong leadership and control by the central government. In particular, a large part of the research and development of science and technology related to the Fourth Industrial Revolution in North Korea is controlled and absorbed by the defense organizations under the national defense-oriented policy framework, among which North Korea is making national efforts to develop advanced technologies in artificial intelligence and actively utilize them in the military affairs. The future weapon system based on AI will have superior performance and destructive power that is different from modern weapons systems, which is likely to change the paradigm of the future battlefield, so a thorough analysis and prediction of the level of AI militarization technology, the direction of development, and AI-based weapons system in North Korea is needed. In addition, research and development of South Korea's corresponding weapon systems and military science and technology are strongly required as soon as possible. Therefore, in this paper, we will analyze the level of AI technology, the direction of AI militarization, and the AI-based weapons system in North Korea, and discuss the AI military technology and corresponding weapon systems that South Korea military must research and develop to counter the North Korea's. The next study will discuss the analysis of AI militarization technologies not only in North Korea but also in neighboring countries in Northeast Asia such as China and Russia, as well as AI weapon systems by battlefield function, detailed core technologies, and research and development measures.

Survey of Recent Research in Education based on Artificial Intelligence (AI 기반 교육 현황과 기술 동향)

  • Jeon, H.B.;Chung, H.;Kang, B.O.;Lee, Y.K.
    • Electronics and Telecommunications Trends
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    • v.36 no.1
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    • pp.71-80
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    • 2021
  • Artificial intelligence (AI) will have a huge impact on future education. We look at the role of AI in education and changes in schools. Personalized education is being attempted in limited services, and an interactive tutor service with speech recognition/dialog technology is being developed. In the future, we look forward to fully personalized education for individual students through AI teachers. Teachers are expected to make more effort to teach creative thinking, critical thinking, communication, and collaboration. As the speed of development of AI technology accelerates, we expect that AI-based education will be deeply established around us in the near future. We first introduce the details of the personalization technology and then discuss the AI-based foreign language speaking education research conducted by ETRI.

Transforming Text into Video: A Proposed Methodology for Video Production Using the VQGAN-CLIP Image Generative AI Model

  • SukChang Lee
    • International Journal of Advanced Culture Technology
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    • v.11 no.3
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    • pp.225-230
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    • 2023
  • With the development of AI technology, there is a growing discussion about Text-to-Image Generative AI. We presented a Generative AI video production method and delineated a methodology for the production of personalized AI-generated videos with the objective of broadening the landscape of the video domain. And we meticulously examined the procedural steps involved in AI-driven video production and directly implemented a video creation approach utilizing the VQGAN-CLIP model. The outcomes produced by the VQGAN-CLIP model exhibited a relatively moderate resolution and frame rate, and predominantly manifested as abstract images. Such characteristics indicated potential applicability in OTT-based video content or the realm of visual arts. It is anticipated that AI-driven video production techniques will see heightened utilization in forthcoming endeavors.

Comparative Analysis of AI Painting Using [Midjourney] and [Stable Diffusion] - A Case Study on Character Drawing -

  • Pingjian Jie;Xinyi Shan;Jeanhun Chung
    • International Journal of Advanced Culture Technology
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    • v.11 no.2
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    • pp.403-408
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    • 2023
  • The widespread discussion of AI-generated content, fueled by the emergence of consumer applications like ChatGPT and Midjourney, has attracted significant attention. Among various AI applications, AI painting has gained popularity due to its mature technology, user-friendly nature, and excellent output quality, resulting in a rapid growth in user numbers. Midjourney and Stable Diffusion are two of the most widely used AI painting tools by users. In this study, the author adopts a perspective that represents the general public and utilizes case studies and comparative analysis to summarize the distinctive features and differences between Midjourney and Stable Diffusion in the context of AI character illustration. The aim is to provide informative material forthose interested in AI painting and lay a solid foundation for further in-depth research on AI-generated content. The research findings indicate that both software can generate excellent character images but with distinct features.

An Efficient Second-hand transaction meta-services (효율적인 중고거래 메타서비스)

  • Sewoong Hwang;Min-Taek LIm;Hyun-Ki Hong;Hun-Tae Hwang;Sung-Hyun Park;Young-Kyu Choi;Suk-Hyung Hwang;Soo-Hwan Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.469-471
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    • 2023
  • 본 논문에서는 기존 중고거래 플랫폼들의 불편한 점들을 해소하고 사용자들이 효율적이고 편리한 중고거래를 할 수 있도록 도와주는 플랫폼을 개발했다. 조사를 통해 기존 중고거래 플랫폼은 허위 매물, 시세 파악의 어려움, 사기 피해 등의 문제점이 존재한다는 사실을 인식했다. 문제 해결을 위해 파이썬을 활용하여 주요 중고거래 플랫폼의 상품 데이터를 수집했다. 이에 IQR을 적용하여 가격의 이상치를 판별했다. 가격 비교와 허위 매물 판별이 용이하게 되는 장점이 있다. 또한 이상치를 제거한 상품들의 시세를 계산하여 데이터를 차트로 시각화했다. 플랫폼과 지역마다 상이한 중고 상품의 신뢰성 있는 시세를 파악할 수 있고 중고거래 사기 피해를 방지할 수 있도록 사용자에게 주요 사기 수법, 뉴스 등의 정보를 제공한다.

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Impact of Artificial Intelligence on the Development of Art Projects: Opportunities and Limitations

  • Zheng, Xiang;Xiong, Jinghao;Cao, Xiaoming;Nazarov, Y.V.
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.343-347
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    • 2022
  • To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

Dr. Vegetable: an AI-based Mobile Application for Diagnosis of Plant Diseases and Insect Pests (농작물 병해충 진단을 위한 인공지능 앱, Dr. Vegetable)

  • Soohwan Kim;DaeKy Jeong;SeungJun Lee;SungYeob Jung;DongJae Yang;GeunyEong Jeong;Suk-Hyung Hwang;Sewoong Hwang
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.457-460
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    • 2023
  • 본 연구는 시설작물의 병충해 진단을 위해 딥러닝 모델을 응용한 인공지능 서비스 앱, Dr. Vegetable을 제안하고자 한다. 농업 현장에서 숙련된 농부는 한눈에 농작물의 병충해를 판단할 수 있지만 미숙련된 농부는 병충해 피해를 발견하더라도 그 종류와 해결 방법을 찾아내기가 매우 어렵다. 또한 아무리 숙련된 농부라고 할지라도 육안검사만으로 병충해를 조기에 발견하는 것은 쉽지 않다. 한편 시설작물의 경우 병충해에 의한 연쇄피해가 발생할 우려가 있으므로 병충해의 조기 발견 및 방제가 매우 중요하다. 즉, 농부의 경험에 따른 농작물 병해충 진단은 정확성을 장담할 수 없으며 비용과 시간적인 측면에서 위험성이 높다고 할 수 있다. 본 논문에서는 YOLOv5를 활용하여 상추, 고추, 토마토 등 농작물의 병충해를 진단하는 인공지능 서비스를 제안한다. 특히 한국지능정보사회진흥원이 운영하고 있는 AI 통합 플랫폼인 AI 허브에서 제공하는 노지 작물 질병 및 해충 진단 이미지를 사용하여 딥러닝 모델을 학습하였다. 본 연구를 통해 개발된 모바일 어플리케이션을 이용하여 실제 시설농장에서 병충해 진단 서비스를 적용한 결과 약 86%의 정확도, F1 Score 0.84, 그리고 0.98의 mAP 값을 얻을 수 있었다. 본 연구에서 개발한 병충해 진단 딥러닝 모델을 다양한 조도에서 강인하게 동작하도록 개선한다면 농업 현장에서 널리 활용될 수 있을 것으로 기대한다.

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Design of an Improved AI PigMoS System based on Mobile Web (모바일 웹기반 개선된 AI PigMoS 시스템의 설계)

  • Kim, Hyun-ju;Son, Yong-sook;Kim, Bong-Gi;Kim, Heung-Jun;Lee, Gwang-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.701-702
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    • 2013
  • 전국 50여개의 AI(Artificial Insemination)센터는 국내 양돈산업 인공수정 기술을 개발하고 보급하는 중추적인 역할을 수행하고 있다. 이에 반해 AI센터의 숫자 규모는 전국적으로 매우 제한되어 있어, AI센터의 운영 및 AI 기술에 대한 정보관리는 각 센터별 독자적인 운영시스템으로 관리되어 상호 정보융합을 통한 양돈산업 발전에 활용되는 사례가 매우 적다. 또한 개별 AI센터에서 관리하고 있는 소비자들의 지역분포도가 매우 폭넓어 실시간으로 수요자에 대한 판매 관리정보를 제공함에 있어 그 한계를 가지고 있다. 이에 본 논문에서는 전국의 AI센터 관리운영에 통합적이고 효율성을 지원할 수 있는 모바일 웹기반 개선된 AI PigMoS(Pig Monitoring System, PigMoS) 시스템을 제안하고 구현하였다. 본 논문에서 제안한 모바일 웹기반 개선된 AI PigMoS 시스템은 이동성, 실시간 정보서비스 등에 해당되는 시스템 모듈을 모바일 웹을 기반으로 구현하여 개별 AI센터에서 운영할 수 있게 하였다. 이에 본 논문에서는 기존의 AI PigMoS 시스템을 개선하여 재구축하였으며, 이동성, 실시간 정보서비스 등이 필요한 모듈을 중심으로 모바일 기능을 설계하고 구현하여, 원거리 소비자들에게 실시간으로 생성된 AI정보를 제공하여 AI센터의 정보관리 효율성과 경쟁력 향상을 높일 것으로 기대한다.

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Competitiveness Analysis for Artificial Intelligence Technology through Patent Analysis (특허분석을 통한 인공지능 기술 분야 경쟁력 분석: 특허 시장성과 기술력 질적 분석을 중심으로)

  • Kwak, Hyun;Lee, Seongwon
    • The Journal of Information Systems
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    • v.28 no.3
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    • pp.141-158
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    • 2019
  • Purpose Artificial Intelligence (AI) is a core technology, leading the 4th industrial revolution. This study aims to diagnose the Korean's national competitiveness for AI technologies through patent analyses. Design/methodology/approach In this study, KIWEE and Derwent Innovation databases were used as data source of patents. we extracted 10,510 AI patents data with keywords and classified them into 15 subcategories of AI technology. We executed patent analyses for activity index, patent intensity index, technology strength, and patent family size and diagnosed Korea's national competitiveness in AI industry. Findings The results showed that Korea is less competitive than the United States and Japan in AI industry. However, patent amount has increased since 2010, which is encouraging result. This study has implication on the need for human and R&D investment in AI industry.

Development of Radar-enabled AI Convergence Transportation Entities Detection System for Lv.4 Connected Autonomous Driving in Adverse Weather

  • Myoungho Oh;Mun-Yong Park;Kwang-Hyun Lim
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.190-201
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    • 2023
  • Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.