• Korean Journal of Applied Biomechanics
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• v.34 no.2
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• pp.71-80
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• 2024

Objective: This study aimed to explore the brain connectivity between brain and biomechanical variables by exploring motion recognition through FFT (fast fourier transform) analysis and AI (artificial intelligence) focusing on quiet standing movement patterns. Method: Participants included 12 young adult males, comprising university students (n=6) and elite gymnasts (n=6). The first experiment involved FFT of biomechanical signals (f_CoP, f_AJtorque and f_EEG), and the second experiment explored the optimization of AI-based GRU (gated recurrent unit) using f_EEG data. Results: Significant differences (p<.05) were observed in frequency bands and maximum power based on group and posture types in the first experiment. The second study improved motion prediction accuracy through GRU performance metrics derived from brain signals. Conclusion: This study delved into the movement pattern of upright standing posture through the analysis of bio-signals linking the cerebral cortex to motor performance, culminating in the attainment of motion recognition prediction performance.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.319-324
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• 2024

In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

• Korean Journal of Artificial Intelligence
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• v.10 no.2
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• pp.1-6
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• 2022

In this paper, the research and development aim to strengthen the digital accessibility of the elderly by developing a kiosk incorporating AI voice recognition technology that can replace the promotional signage currently being installed and spread in the elderly and social welfare centers most frequently used by the digital underprivileged. It was intended to develop a converged system for the use of bulletin board functions, educational functions, and welfare center facilities, and to seek ways to increase the user's digital device experience through direct experience and education. Through interviews and surveys of senior citizens and social welfare centers, it was intended to collect problems and pain Points that the elderly currently experience in the process of using kiosks and apply them to the development process, and improve problems through pilot services. Through this study, it was confirmed that voice recognition technology is 2 to 6 times faster than keyboard input, so it is helpful for the elderly who are not familiar with device operation. However, it is necessary to improve the problem that there is a difference in the accuracy of the recognition rate according to the surrounding environment with noise. Through small efforts such as this study, we hope that the elderly will be a little free from digital alienation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.445-446
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• 2022

In this paper, in order to improve port work preparation and berth scheduling efficiency in an artificial intelligence-based berthing monitoring system that can monitor the ship's berthing process, we develop a mooring line recognition model to check an exact berthing time. By improving the pre-designed AI model, it is possible to segment the mooring line from the input image, and to recognize when the mooring line arrives or falls on the berth, thereby providing the correct ship's berthing time. The proposed AI model confirmed by the results that mooring line recognition is possible with evaluation data about the actual berthing situation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.77-78
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• 2024

본 논문에서는 O2O 상점의 자동화에 필수적인 객체 인식 모델의 성능 향상을 목표로, 생성 AI 기술을 이용한 데이터 증강 방법을 제시한다. 제안하는 방법은 텍스트 프롬프트를 활용하여 진열대 상품 이미지를 포함한 다양한 고품질 이미지를 생성할 수 있음을 보인다. 또한, 실제에 더 가까운 상세한 이미지를 생성하기 위한 최적화된 프롬프트를 제안하고, Stable-Diffusion과 DALL-E2의 생성 결과를 통해 비교 분석한다. 이러한 접근 방법은 객체 인식 모델의 성능 향상에 영향을 미칠 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.69-76
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• 2022

In this paper, we presented the contents and methods of AI classes using AI platforms. First, we extracted the content elements of each stage of the AI class using the AI education platform from experts. Classes using the AI education platform were divided into 5 stages and 25 class elements were selected. We also conducted a survey of 82 teachers and analyzed the factors that they acted importantly at each stage of the AI platform class. As a result of the analysis, teachers regarded the following contents as important factors for each stage that are AI model preparation stage (the learning stage of the AI model), problem recognition stage (identification of problems and AI solution potential), data processing stage (understanding the types of data), AI modelingstage (AI value and ethics), and problem solvingstage (AI utilization in real life).

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.814-817
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• 2020

The number of single-person households is increasing every year, and there are also high concerns about the crime and safety of single-person households. In particular, crimes targeting women are increasing. Although home surveillance camera applications, which are mostly used by single-person households, only provide intrusion detection functions, this service utilizes AI image recognition technologies such as face recognition and object detection to provide theft, violence, stranger and intrusion detection. Users can receive security-related notifications, relieve their anxiety, and prevent crimes through this service.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.60-69
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• 2022

So far, artificial intelligence (AI)/machine learning (ML) has produced impressive results in speech recognition, computer vision, and natural language processing. AI/ML has recently begun to show promise as a viable means for improving the performance of 5G mobile telecommunication systems. This paper investigates standardization activities in 3GPP and O-RAN Alliance regarding AI/ML applications on mobile telecommunication system. Future trends in AI/ML technologies are also summarized. As an overarching technology in 6G, there appears to be no doubt that AI/ML could contribute to every part of mobile systems, including core, RAN, and air-interface, in terms of performance enhancement, automation, cost reduction, and energy consumption reduction.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.598-600
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• 2023

CCTV가 범죄 예방 및 수사에 사용되는데, 수사를 위해 저화질 CCTV 영상에서 특정인의 얼굴 인식엔 어려움을 겪어 CCTV 본연의 역할의 희석된다. 따라서 본 논문은 저화질 영상을 고화질로 변환하여 얼굴 인식의 정확성을 높일 수 있는 알고리즘을 연구하는 것을 목적으로 한다. 기존에 연구된 인공지능 기반의 업스케일링 알고리즘을 분석하여 K-FACE 데이터셋에 적절한 모델을 제안한다. 이를 위해 2020년 이전과 이후의 AI 업스케일링 관련 연구를 비교 분석한다. 향후 제시된 모델을 대상으로 동일한 환경내에서 K-FACE 데이터셋을 학습시켜 통일된 기준의 지표 산출이 필요하다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.47-52
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• 2021

Recently, demand for artificial intelligence solutions for production process management has been increasing in the manufacturing industry. However, through the application of AI solutions in the manufacturing industry, there are limitations to legacy smart factory solutions such as POP and MES.Therefore, in order to overcome this, this paper aims to improve production management efficiency by applying guidance, an artificial intelligence concept, to image recognition systems. In the system flow, As_is To be separated and actual work flow was applied, and the process was improved for overall productivity efficiency. The pre-processing plan for AI guidance learning was established and the relevant AI model was designed, developed, and simulated, resulting in a 97% recognition rate.