• Korean Journal of Child Studies
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• v.37 no.4
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• pp.17-29
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• 2016

Objective: The purpose of this study was to examine the bidirectional relation between mobile phone dependency (MPD) and self-regulated learning (SRL) of early Korean adolescents in $4^{th}$, $6^{th}$ and $8^{th}$ grade, while taking into account gender differences. Methods: The study made use of panel data from the Korean Children and Youth Panel Study (KCYPS), and three waves of data collected from 2,264 adolescents were analyzed by means of autoregressive cross-lagged modeling. Results: The results can be summarized as follows. Firstly, MPD and SRL were consistently stable for adolescents in $4^{th}$, $6^{th}$ to $8^{th}$ grades. Secondly, a bidirectional relations between MPD and SRL were confirmed. In other words, there was a significant influence of a high level of MPD on a subsequent low level of SRL, and the high level of SRL also had a significant effect on the lower level of MPD across time. According to multi-group analysis, no gender differences were found in the relations between two constructs during the studied period. Conclusion: Findings highlighted not only the necessary media usage education but also parenting intervention strategies may help early adolescents to be prevented from negative effects of media usage and to enhance self-regulated learning ability. Based on the results, more implications were also discussed.

• Broadcasting and Media Magazine
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• v.25 no.2
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• pp.17-26
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• 2020

최근 스마트폰에서의 증강현실, 미적 효과의 증대(예, 라이브 포커싱) 등의 어플리케이션을 제공하기 위해 모바일 기기에서의 3차원 공간 복원 기술에 대한 관심이 증가하고 있다. 소비자들의 요구에 발 맞춰 최근 스마트폰 제조사는 모든 플래그십 모델에 다중 카메라 및 뎁스 센서(거리 측정 센서)를 탑재하는 추세이다. 본 고에서는 모바일 폰에 탑재되고 있는 대표적인 세 축의 뎁스 추정(공간 복원) 방식에 대해 간단히 살펴보고, 최근 심층학습(Deep learning)의 등장으로 기술 발전의 새로운 국면에 접어 든 다중 시점 매칭(Multi-view stereo) 방법에 대해 소개하고자 한다. 심층 신경망이 재조명 받은 2012년 전까지 주류 연구 방향이었던 전통 기하학 기반의 방법에 대한 소개를 시작으로 심층 신경망기반의 방법론으로의 발전된 형태를 살펴본다. 또한, 신경망기반의 방법론은 크게 3 세대로 나누어 각 세대별 특징에 대해 자세히 살펴보고, 다양한 데이터에 대한 실험 결과를 통해 세대별 공간 복원 결과를 비교 분석한다.

• 한국HCI학회:학술대회논문집
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• 2007.02c
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• pp.322-325
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• 2007

Graphics processing unit (GPU) is used for a faster artificial neural network. It is used to implement the matrix multiplication of a neural network to enhance the time performance of a text detection system. Preliminary results produced a 20-fold performance enhancement using an ATI RADEON 9700 PRO board. The parallelism of a GPU is fully utilized by accumulating a lot of input feature vectors and weight vectors, then converting the many inner-product operations into one matrix operation. Further research areas include benchmarking the performance with various hardware and GPU-aware learning algorithms. (c) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1261-1264
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• 2022

최근 본인에게 어울리는 색상을 배경으로 촬영하는 감성 증명사진이 유행하고 있다. 개인마다 퍼스널 컬러를 찾아 배경색에 적용하는 것은 시간, 비용, 인력적으로 어려움이 있으므로 자동으로 개인에 따른 배경색을 찾아서 사진을 합성하여 감성 증명사진을 제작해 주는 딥러닝 기반 시스템을 구축하였다. 본 논문에서는 Convolution Neural Network 를 기반으로 한 딥러닝 기술을 이용해 Image Matting 과 Multi-Label Classification 을 수행하여 기존 감성 증명사진들을 학습하여 모델을 구축하였으며, 해당 시스템으로 사용자에게 새로운 배경색이 적용된 감성 증명사진을 제공하는 웹 애플리케이션을 제안한다.

• Smart Media Journal
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• v.13 no.2
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• pp.23-31
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• 2024

In precision cattle farm, reliably tracking the identity of each cattle is necessary. Effective tracking of cattle within farm environments presents a unique challenge, particularly with the need to minimize the occurrence of excessive tracking trajectories. To address this, we introduce a trajectory playback decision tree algorithm that reevaluates and cleans tracking results based on spatio-temporal relationships among trajectories. This approach considers trajectory as metadata, resulting in more realistic and accurate tracking outcomes. This algorithm showcases its robustness and capability through extensive comparisons with popular tracking models, consistently demonstrating the promotion of performance across various evaluation metrics that is HOTA, AssA, and IDF1 achieve 68.81%, 79.31%, and 84.81%.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.67-70
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• 2018

Object detection and tracking is an exciting and interesting research area in the field of computer vision, and its technologies have been widely used in various application systems such as surveillance, military, and augmented reality. This paper proposes and implements a novel and more robust object recognition and tracking system to localize and track multiple objects from input images, which estimates target state using the likelihoods obtained from multiple CNNs. As the experimental result, the proposed algorithm is effective to handle multi-modal target appearances and other exceptions.

• Educational Technology International
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• v.12 no.1
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• pp.1-20
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• 2011

The study described in this paper examined the effectiveness of a multimedia case-based learning environment to teach technology integration to Korean pre-service teachers. The structure and philosophy behind the use of embedded video in an online, multimedia system and the data collected from 103 pre-service teachers are presented and discussed. The overall finding shows that there was no significant difference from pre- to posttest among the lecture, the case-based, and the mixed environment groups. However, low prior knowledge students improved more when they learned about technology integration with the mixed method than with the case-based method alone. Discussion about this result and its educational implications conclude the paper.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1569-1577
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• 2015

Recently, the development of IT technology, utilization of smart devices 3-5-year-old infants Upon smart device penetration rate per household increases has also sharply increased. In this paper, the educational contents for kid are considered and implemented by reflecting this trend. Content that has been produced in this paper are based on learning theory of constructivism, was to be performed naturally learn the content of the table-top display of applying the NUI technology. Also, the content creation that can help you learn infants through experiments crafted tabletop display interface content, it is believed to be the basis for the improvement of usability.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.1-3
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• 2022

최근 기존의 영상 압축 파이프라인 대신 신경망의 종단 간 학습을 통해 압축을 수행하는 알고리즘의 연구가 활발히 진행되고 있다. 본 논문은 종단 간 학습 기반 공간적 스케일러블 압축 기술을 제안한다. 보다 구체적으로 본 논문은 신경망의 각 계층에서 하위 계층의 학습된 특징 (feature)을 융합하여 상위 계층으로 전달하는 다중 스케일 특징 융합 (multi-scale feature fusion) 모듈을 도입해 상위 계층이 더욱 풍부한 특징 정보를 학습하고 계층 사이의 특징 중복성을 더욱 잘 제거할 수 있도록 한다. 기존 방법 대비 향상 계층(enhancement layer)에서 1.37%의 BD-rate가 향상된 결과를 볼 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.420-424
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• 2016

Recently, with the development of Internet technology and multi-media technology, the Internet is going to develop in many areas, a new application areas. In particular, in the area of education, has made a Epoch-making development in the Internet applications, it has presented the instructional methods of the new paradigm. Study using the online learning, instructional method of a conventional traditional new proposal that deviates from the off-line teaching, Unlike the existing off-line learning, without being bound by time and space, in terms of anytime, anywhere it is possible to attend the lecture, is a very efficient learning. Online lectures Despite many advantages, and containing a number of problems. In terms of space of the learning is performed on-line, there is a disadvantage that the student management and learning, the reliability of evaluation missing number. In this study, out of such a variety of problems, concentration to induce an active learning attitude of learners, learners of learning who attempt to increase the reliability and using the face detection system of attendance learning It proposed a degree system.