• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1403-1408
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• 2010

Korean information retrieval uses noun as index terms or keywords of representing the document. and noun and keyword extraction is to find all nouns presented in the document, In this paper, we proposes the method of keyword extraction using pre-built dictionary. This method reduces the execution time by reducing unnecessary operations. And noun, even large documents without affecting significantly the accuracy, can be extracted. This paper proposed noun extraction method using the appearance characteristics of the noun and keyword extraction method using unsupervised learning techniques.

• Journal of Engineering Education Research
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• v.4 no.2
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• pp.35-44
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• 2001

Recently, according to the appearance of various virtual websites using multimedia technologies for engineering education, the internet applications in engineering education have drawn much interests. But unidirectional communication, simple text/image-based webpages and tedious learning process without motivation etc. have made the lowering of educational efficiency in cyberspace. Thus, to cope with these difficulties this paper presents a web-based educational Java applets for understanding the principles or conceptions of digital logic systems. The proposed Java applets provides the improved learning methods which can enhance the interests of learners. The results of this paper can be widely used to improve the efficiency of cyberlectures in the cyber university. Several sample Java applets are illustrated to show the validity of the proposed learning method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.165-166
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• 2010

Noun extraction is to find all nouns presented in the document, Korean information retrieval uses noun as index terms or keywords of representing the document. In this paper, we proposes the method of keyword extraction using pre-built dictionary. This method reduces the execution time by reducing unnecessary operations. And noun, even large documents without affecting significantly the accuracy, can be extracted. This paper proposed noun extraction method using the appearance characteristics of the noun and keyword extraction method using unsupervised learning techniques.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.3
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• pp.29-44
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• 2021

The study provides a quantitative and qualitative description of global research in the domain of quantum machine learning (QML) as a way to understand the status of global research in the subject at the global, national, institutional, and individual author level. The data for the study was sourced from the Scopus database for the period 1999-2020. The study analyzed global research output (1374 publications) and global citations (22434 citations) to measure research productivity and performance on metrics. In addition, the study carried out bibliometric mapping of the literature to visually represent network relationship between key countries, institutions, authors, and significant keyword in QML research. The study finds that the USA and China lead the world ranking in QML research, accounting for 32.46% and 22.56% share respectively in the global output. The top 25 global organizations and authors lead with 35.52% and 16.59% global share respectively. The study also tracks key research areas, key global players, most significant keywords, and most productive source journals. The study observes that QML research is gradually emerging as an interdisciplinary area of research in computer science, but the body of its literature that has appeared so far is very small and insignificant even though 22 years have passed since the appearance of its first publication. Certainly, QML as a research subject at present is at a nascent stage of its development.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.1
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• pp.1-11
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• 2014

In this paper we propose a system for vehicle detection and tracking which has the ability to learn on-line appearance changes of vehicles being tracked. The proposed system uses feature-based tracking method to estimate rapidly and robustly the motion of the newly detected vehicles between consecutive frames. Simultaneously, the system trains an online vehicle detector for the tracked vehicles. If the tracker fails, it is re-initialized by the detection of the online vehicle detector. An improved vehicle appearance model update rule is presented to increase a tracking performance and a speed of the proposed system. Performance of the proposed system is evaluated on the dataset acquired on various driving environment. In particular, the experimental results proved that the performance of the vehicle tracking is significantly improved under bad conditions such as entering a tunnel and passing rain.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.609-620
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• 2016

Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.271-274
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• 2006

This paper deals with a similarity decision method between the shape of hand-postures and their structures to improve performance of the vision-based hand-posture recognition system. Hand-posture recognition by vision sensors has difficulties since the human hand is an object with high degrees of freedom, and hence grabbed images present complex self-occlusion effects and, even for one hand-posture, various appearances according to viewing directions. Therefore many approaches limit the relative angle between cameras and hands or use multiple cameras. The former approach, however, restricts user's operation area. The latter requires additional considerations on the way of merging the results from each camera image to get the final recognition result. To recognize hand-postures, we use both of appearance and structural features and decide the similarity between the two types of features by learning.

• Journal of Korean Home Economics Education Association
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• v.24 no.3
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• pp.101-122
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• 2012

The purpose of this study is to develop teaching learning process plans with problem-based learning using book-making applying to the "Dressing and Self Expression" unit and evaluate its effect in middle school home economics for first grade. We developed teaching learning process plans with problem-based learning using book-making including 9 teaching materials for teachers and 15 learning materials for students. Further, we conducted and investigated pre- and post-tests in a form of questionnaires in 167 students from a girls' middle school in Pusan. Teaching learning process plans with problem-based learning using book-making showed positive results in body satisfaction, such as reduction in distortion or less dissatisfaction regarding students' body images. Also, they were found to be less affected by sociocultural attitude towards appearance. The estimation of students included the positive contents that the class was interested with various materials and it provided them with a chance to understand their body. Meanwhile, minor comments pointed out lack of time and complained of the amount of assignments. With these results, we found that teaching learning process plans with problem-based learning using book-making was an appropriate model to achieve the purpose of this study and we suggested that this class might be applied to other units of middle school home economics.

• Journal of Engineering Education Research
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• v.5 no.1
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• pp.27-33
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• 2002

Recently, according to the appearance of various virtual websites using multimedia technologies, the internet applications in engineering education have drawn muchinterests. But unidirectional communication, simple text/image-based webpages and tedious learning process without motivation, etc. have made the lowering of educational efficiency in cyberspace. This paper presents a virtual laboratory system which can be creating efficiencies in the learning process. The proposed virtual laboratory system for digital logic circuits provides interactive learning environment under which the multimedia capabilities of world-wide web can be enhanced. The virtual laboratory system is implemented to describe the on-campus laboratory, the learners can obtain similar experimental data through it. The virtual laboratory system is composed of four important components : principle classroom, simulation classroom, virtual experiment classroom and management system. Learning efficiencies as well as faculty productivity are increased in this innovative teaching and learning environment.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.19-28
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• 2022

In this paper, we propose the Detector Scheduler which determines the best tracking-by-detection (TBD) mechanism to perform real-time high-accurate multi-object tracking (MOT). The Detector Scheduler determines whether to run a detector by measuring the dissimilarity of features between different frames. Furthermore, we propose a self-supervision method to learn the Detector Scheduler with tracking results since it is difficult to generate ground truth (GT) for learning the Detector Scheduler. Our proposed self-supervision method generates pseudo labels on whether to run a detector when the dissimilarity of the object cardinality or appearance between frames increases. To this end, we propose the Detector Scheduling Loss to learn the Detector Scheduler. As a result, our proposed method achieves real-time high-accurate multi-object tracking by boosting the overall tracking speed while keeping the tracking accuracy at most.