• 제목/요약/키워드: appearance learning

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중국 대학생의 동영상 학습에서 교수자 출연이 학습자 행동유형에 따라 학습몰입과 교수실재감에 미치는 효과 (Effects of Lecturer Appearance and Students' Behavioral Patterns on Learning Flow and Teaching Presence of Chinese University Students' Video Lectures)

  • 태효하;제혜금;김보경
    • 한국융합학회논문지
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    • 제12권3호
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    • pp.107-114
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    • 2021
  • 본 연구의 목적은 중국 대학생의 동영상 학습에서 교수자 출연이 학습자 행동유형에 따라 학습몰입과 교수실재감에 미치는 효과를 분석하는 것이다. 중국 형태대학교 183명의 학생을 대상으로 DISC 행동유형을 분류한 후 교수가 출연과 마출연 동영상에 배정하여 학습하게 하였다. 이후 학습몰입과 교수실재감을 측정한 후 집단 간 차이를 분석하였다. 연구결과, 교수자가 출연하는 강의동영상을 학습한 집단이 학습몰입과 교수실재감이 높게 나타났다. 둘째, 교수자 출연여부가 학습자 행동유형에 따라 학습몰입에 미치는 효과에서는 교수자 출연의 효과는 유의하였으나 둘의 상호작용 효과는 유의하지 않았다. 셋째, 교수자 출연여부가 학습자 행동유형에 따라 교수실재감에 미치는 효과에서 교수자 출연의 효과는 유의하였고, 학습자 행동유형의 효과는 유의하지 않았지만, 둘의 상호작용 효과는 유의하였다. 이러한 연구결과는 강의동영상은 교수자가 출연하는 것이 좋으며, 교수실재감을 높이기 위해 학습자의 행동유형의 상호작용효과를 고려하여 교수자 출연여부를 결정하는 것이 효과적임을 시사한다.

Robust appearance feature learning using pixel-wise discrimination for visual tracking

  • Kim, Minji;Kim, Sungchan
    • ETRI Journal
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    • 제41권4호
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    • pp.483-493
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    • 2019
  • Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

동영상 학습에서 교수자 출연여부와 발화속도가 학습몰입과 교수실재감에 미치는 효과 (Effects of Lecturer Appearance and Speech Rate on Learning Flow and Teaching Presence in Video Learning)

  • 태효하;제혜금;김보경
    • 한국산학기술학회논문지
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    • 제22권1호
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    • pp.267-274
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    • 2021
  • 본 연구는 동영상 학습에서 교수자 출연 여부와 교수자 발화속도가 학습몰입과 교수실재감의 효과에 차이를 나타내는지를 실험을 통해 밝히는 것이다. 실험 대상자는 중국 형태대학교 1학년 183명이며, 이들에게 교수자가 출연여부와 발화속도 고저의 4가지 동영상을 학습하도록 한 후, 학습몰입과 교수실재감을 측정하였다. 수집된 자료는 다변량분산분석을 통해 분석하였다. 분석결과 첫째, 교수자가 출연한 동영상을 학습한 집단이 그렇지 않은 집단보다 학습몰입과 교수실재감이 모두 높게 나타났다. 둘째, 교수자의 발화속도가 높은 동영상으로 학습한 집단이 낮은 동영상으로 학습한 집단보다 학습몰입과 교수실재감이 모두 높게 나타났다. 셋째, 교수자 출연여부와 발화속도의 학습몰입과 교수실재감에 대한 상호작용 효과는 유의한 차이가 없는 것으로 나타났다. 이러한 연구결과는 대학 수업에서 효과적인 학습을 위한 강의 동영상을 개발할 때 교수자의 출연여부와 발화속도를 어떻게 설계할 것인지에 대한 이론적·실천적 근거를 제공한다. 즉 가급적 동영상에 교수자가 출연하여 표정, 몸짓과 같은 비언어적 방식으로 사회적 단서를 제시하는 것이 중요하다. 또한 교수자는 동영상에서 약간 빠른 속도로 설명함으로써 학생이 학습에 더 집중하여 몰입하게 할 수 있다. 교수자 출연과 빠른 발화속도는 학습에 몰입하게 하고, 동영상에서 교수행위가 실재로 이루어지고 있다는 느낌을 주게 한다는 것을 시사한다.

POSE-VIWEPOINT ADAPTIVE OBJECT TRACKING VIA ONLINE LEARNING APPROACH

  • Mariappan, Vinayagam;Kim, Hyung-O;Lee, Minwoo;Cho, Juphil;Cha, Jaesang
    • International journal of advanced smart convergence
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    • 제4권2호
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    • pp.20-28
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    • 2015
  • In this paper, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame with posture variation and camera view point adaptation by employing the non-adaptive random projections that preserve the structure of the image feature space of objects. The existing online tracking algorithms update models with features from recent video frames and the numerous issues remain to be addressed despite on the improvement in tracking. The data-dependent adaptive appearance models often encounter the drift problems because the online algorithms does not get the required amount of data for online learning. So, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame.

Effects of Instructor's Communication Quality on Learning Flow and Satisfaction of Students: Targeting the Students(Parents) Participating in the Early Childhood Education Programs

  • Kim, Hee-Jung;Kim, Joon-Ho
    • 품질경영학회지
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    • 제43권2호
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    • pp.201-218
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    • 2015
  • Purpose: This study surveyed the effects of instructors' verbal and nonverbal communication quality on students' learning flow and satisfaction. We divided the two types of communication into sub-factors - verbal communication into language, and nonverbal communication into kinesics, proxemics, paralanguage and physical appearance - to examine the causal relationship between learning flow and learning satisfaction. Methods: This study was conducted on the students (parents) of a paid early childhood education program run by "I" company located in Seoul, from November 12, 2014 to November 18, 2014. A total of 317 (90.5 %, effective) questionnaires were collected and analyzed using SPSS 18.0 and AMOS 18.0. Results: First, the verbal communication of the lecturers was found to have significantly positive (+) effects on learning satisfaction. Second, among the nonverbal communications, proxemics and physical appearance were found to have positive (+) effects on learning flow. Third, among the nonverbal communications, proxemics was found to have positive (+) effects on learning satisfaction. Fourth, the learning flow of students was found to have positive (+) effects on learning satisfaction. Conclusion: This study's findings can contribute to realizing desirable communication between instructors and students.

육미지황탕(六味地黃湯)이 국소뇌허혈유발 기억장애(記憶障碍) 모델 흰쥐에 미치는 영향 (Effect of Yukmijihwangtang on Learning and Memory Impairment in Transient Focal Cerebral Ischemia Rat Model)

  • 김기현;민상연;김장현
    • 대한한의학회지
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    • 제30권2호
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    • pp.1-16
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    • 2009
  • Objectives: This study investigated the effect of Yukmijihwangtang on cerebral ischemia-induced learning and memory impairment by middle cerebral artery (MCA) occlusion in rats. Methods: The ability of learning and memory of rats was measured using the eight-arm radial maze and the passive avoidance test, and profile of cholinergic neuron was assessed in the medial septum and hippocampus region by immuno-histochemistry. Results: 1. No differences were found between groups in the number of correct choices in acquisition performance during the eight-arm radial maze task. 2. No differences were found between groups on day 1 in the error rate in acquisition performance, which is defined as the number of enters into the same arm more than once within five minutes. After 5 to 6 days of test, the number of errors was significantly reduced in the Yukmijihwangtang group (forebrain ischemia group with Yukmijihwangtang treatment), compared with the ischemia group. 3. The memory processes significantly improved in the Yukmijihwangtang group according to results of the passive avoidance test. 4. The appearance of AchE (acetylcholinesterase) in the CA1 region of hippocampus significantly decreased in the ischemia group, compared with the sham group (untreated group). The appearance of AchE in the same region significantly increased in the Yukmijihwangtang group, compared with the ischemia group. 5. The appearance of ChAT (choline acetyltransferase) in the CA1 region of the hippocampus and medial septum decreased in the ischemia group, compared with the sham group. The appearance of ChAT in the same region significantly increased in the Yukmijihwangtang group, compared with the ischemia group Conclusions: This study provides evidence that Yukmijihwangtang is effective for reviving the ability of learning and memory and damaged neurons in rats with experimental cerebral ischemia.

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Multi-Cattle tracking with appearance and motion models in closed barns using deep learning

  • Han, Shujie;Fuentes, Alvaro;Yoon, Sook;Park, Jongbin;Park, Dong Sun
    • 스마트미디어저널
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    • 제11권8호
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    • pp.84-92
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    • 2022
  • Precision livestock monitoring promises greater management efficiency for farmers and higher welfare standards for animals. Recent studies on video-based animal activity recognition and tracking have shown promising solutions for understanding animal behavior. To achieve that, surveillance cameras are installed diagonally above the barn in a typical cattle farm setup to monitor animals constantly. Under these circumstances, tracking individuals requires addressing challenges such as occlusion and visual appearance, which are the main reasons for track breakage and increased misidentification of animals. This paper presents a framework for multi-cattle tracking in closed barns with appearance and motion models. To overcome the above challenges, we modify the DeepSORT algorithm to achieve higher tracking accuracy by three contributions. First, we reduce the weight of appearance information. Second, we use an Ensemble Kalman Filter to predict the random motion information of cattle. Third, we propose a supplementary matching algorithm that compares the absolute cattle position in the barn to reassign lost tracks. The main idea of the matching algorithm assumes that the number of cattle is fixed in the barn, so the edge of the barn is where new trajectories are most likely to emerge. Experimental results are performed on our dataset collected on two cattle farms. Our algorithm achieves 70.37%, 77.39%, and 81.74% performance on HOTA, AssA, and IDF1, representing an improvement of 1.53%, 4.17%, and 0.96%, respectively, compared to the original method.

Online Multi-Object Tracking by Learning Discriminative Appearance with Fourier Transform and Partial Least Square Analysis

  • Lee, Seong-Ho;Bae, Seung-Hwan
    • 한국컴퓨터정보학회논문지
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    • 제25권2호
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    • pp.49-58
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    • 2020
  • 본 연구는 온라인 다중 객체 추적 환경에서 모든 객체의 상태(예. 위치 및 크기) 및 identifications (IDs)를 추적하는 문제를 다룬다. 프레임들 간 검출 결과들을 연관하여 객체들의 궤도를 점진적으로 완성하는 tracking-by-detection 접근법을 기반으로 온라인 다중 객체 추적 문제를 해결하고자 한다. 정확한 온라인 연관을 수행하기 위해 이산 푸리에 변환과 부분 최소 제곱법(partial least square, PLS) 분석을 기반으로 하는 새로운 온라인 외형 학습 방법을 제안한다. 즉, 먼저 주파수 도메인에서 추적에 용이한 객체 특징량을 추출하기 위해 추적 객체에 대한 이미지를 푸리에 이미지로 변환한다. 나아가 객체간의 주파수 특징을 보다 잘 구별할 수 있도록 PLS기반 부분 공간을 학습한다. 제안된 외형 학습을 최신 신뢰도 기반 연관 기법과 결합하였고, 다중 객체 추적평가 분야에서 국제적으로 공인된 MOT 벤치마크 챌린지 데이터 셋에서 최신 다중 객체 추적 알고리즘과 비교평가를 수행하였다.

청소년의 자기효능감이 소비행동과 소비생활 단원에 대한 학습효과에 미치는 영향 (The Influence of Juvenile Self-Efficacy on the Consumption Behavior and the Learning Effects of the Unit 'Consumption Life')

  • 박은희
    • 대한가정학회지
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    • 제50권7호
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    • pp.1-12
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    • 2012
  • The purpose of this study was to identify the factor structure of self-efficacy, consumer behavior, and the learning effects of the unit 'Consumption Life' and to study the effects of self-efficacy on the consumer behavior, and the learning effects of the unit 'Consumption Life'. Questionnaires were administered to 370 female middle school students living in the Metropolitan City of Daegu. The data was analyzed by using the frequency, descriptive statistics, factor analysis, reliability analysis, multiple regression, and t-test. The findings are as follow. Self-efficacy was composed of five factors such as the capability in work performance, rational performance, fear, anxiety, and the ability to challenge oneself. Consumer behavior was composed of five factors such as emphasis on product display, emphasis on information, emphasis on fashion, emphasis on appearance, and the products/information exchange. The learning effects of the unit 'Consumption Life' was composed of two factors in the economical consumption, and rational consumption. The effects of consumer behavior and the learning effects of the unit 'Consumption Life' on each of the self-efficacy factors like the capability in work performance, rational performance, fear, anxiety, the ability to challenge oneself were explained by factors such as emphasis on product display, emphasis on information, emphasis on fashion, emphasis on appearance and products/information exchange, and economical consumption and rational consumption.

문맥 정보를 이용한 분류 기반 무릎 뼈 검출 기법 (Classification based Knee Bone Detection using Context Information)

  • 신승연;박상현;윤일동;이상욱
    • 방송공학회논문지
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    • 제18권3호
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    • pp.401-408
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    • 2013
  • 본 논문에서는 영상 내의 문맥 특징(context feature)과 외형 특징(appearance feature)을 함께 학습함으로써 의료영상 내의 비슷한 외형 특징을 가지는 장기들을 자동으로 검출하는 기법을 제안한다. 기존 검출 기법들은 외형 특징 정보만을 학습하여 분류기(classifier)를 생성하였기 때문에 의료영상 내에 외형이 비슷한 장기들이 다수 포함되어 있는 경우 검출 오류가 발생하였다. 제안하는 기법은 외형 특징을 이용하여 학습된 분류기를 통해 얻은 확률 값들을 바탕으로 관심 복셀(voxel) 주변의 확률 분포 특징을 반복적으로 학습함으로써 문맥 정보를 포함하는 분류기를 생성한다. 또한, 실험 단계(test stage)에서 '지역 기반 투표 방식'(region based voting scheme)을 도입함으로써 효율성과 정확성을 향상시킨다. 제안하는 기법의 성능 평가를 위해 SKI10 무릎 관절 데이터 셋 내에서 외형 특징이 비슷한 대퇴골(femur)과 경골(tibia)을 검출하는 실험을 진행하였다. 실험 결과를 통해 제안하는 기법이 외형 특징만을 이용했던 검출 기법에 비해 개선된 검출 성능을 보이고 있음을 확인할 수 있었다.