• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1355-1360
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• 2014

In this paper, we apply the learning of the mobile robot insect augmented reality Digilog Book. In the era of electronic, book written in paper space just have moved to virtual reality space. The virtual reality, constraints spatial and physical, in the real world, it is a technique that enables to experience indirectly situation not experienced directly as user immersive experience type interface. Applied to the learning robot Digilog Book that allows the fusion of paper analog and digital content, using the augmented reality technology, to experience various interactions. Apply critical elements moving, three-dimensional images and animation to enrich the learning, for easier block assembly, designed to grasp more easily rank order between the blocks. Anywhere at any time, is capable of learning of the robot in Digilog Book to be executed by the mobile phone in particular.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.241-244
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• 2014

In this paper, we apply the learning of the mobile robot insect augmented reality Digilog Book. In the era of electronic, book written in paper space just have moved to virtual reality space. The virtual reality, constraints spatial and physical, in the real world, it is a technique that enables to experience indirectly situation not experienced directly as user immersive experience type interface. Applied to the learning robot Digilog Book that allows the fusion of paper analog and digital content, using the augmented reality technology, to experience various interactions. Apply critical elements moving, three-dimensional images and animation to enrich the learning, for easier block assembly, designed to grasp more easily rank order between the blocks. Anywhere at any time, is capable of learning of the robot in Digilog Book to be executed by the mobile phone in particular.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.66-71
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• 2021

본 연구는 한국어 자질 기반 감성분석(Feature-based Sentiment Analysis: FbSA)을 위한 대규모의 학습데이터 구축에 있어 반자동 언어데이터 증강 기법(SSP: Semi-automatic Symbolic Propagation)에 입각한 자질-감성 주석 데이터셋 FeSAD(Feature-Sentiment-Annotated Dataset)의 개발 과정과 성능 평가를 소개하는 것을 목표로 한다. FeSAD는 언어자원을 활용한 SSP 1단계 주석 이후, 작업자의 주석이 2단계에서 이루어지는 2-STEP 주석 과정을 통해 구축된다. SSP 주석을 위한 언어자원에는 부분 문법 그래프(Local Grammar Graph: LGG) 스키마와 한국어 기계가독형 전자사전 DECO(Dictionnaire Electronique du COréen)가 활용되며, 본 연구에서는 7개의 도메인(코스메틱, IT제품, 패션/의류, 푸드/배달음식, 가구/인테리어, 핀테크앱, KPOP)에 대해, 오피니언 트리플이 주석된 FeSAD 데이터셋을 구축하는 프로세싱을 소개하였다. 코스메틱(COS)과 푸드/배달음식(FOO) 두 도메인에 대해, 언어자원을 활용한 1단계 SSP 주석 성능을 평가한 결과, 각각 F1-score 0.93과 0.90의 성능을 보였으며, 이를 통해 FbSA용 학습데이터 주석을 위한 작업자의 작업이 기존 작업의 10% 이하의 비중으로 감소함으로써, 학습데이터 구축을 위한 프로세싱의 소요시간과 품질이 획기적으로 개선될 수 있음을 확인하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.171-176
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• 2022

CNN is a type of deep learning and is a neural network used to process images or image data. The filter traverses the image and extracts features of the image to distinguish the image. Deep learning has the characteristic that the more data, the better models can be made, and CNN uses a method of artificially increasing the amount of data by means of data augmentation such as rotation, zoom, shift, and flip to compensate for the weakness of less data. When learning CNN, we would like to check whether outline image learning is helpful in improving performance compared to conventional data augmentation techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2279-2284
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• 2011

Recently as AR(Augmented Reality) is focus of attention, AR is applied to various fields and is expected its valuable use. In this paper, we suggested the method to combine existing e_Book with augmented reality technology based on mobile equipment. We ascertained that augmented reality contents implemented on PC work well in pITX embedded lines (CPU Intel ATOM Z530) and we implemented augmented reality using marker in e_ Book in pITX embedded lines through these experiments. As the result of it, we could show the contents at the same time which had difficulty to be expressed on e_Book before. Also the existing augmented reality contents could be used as it is. Finally we expected that the user could interact with virtual contents or services directly and intuitively in the real world.

• The Korean Journal of Applied Statistics
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• v.37 no.5
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• pp.599-613
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• 2024

Data augmentation is widely adopted in computer vision. In contrast, research on data augmentation in the field of natural language processing has been limited. We propose several data augmentation methods to support the classification of Korean texts. We increase the size and diversity of text data which are specifically tailored to Korean. These methods adopt and adjust the existing data augmentation for English texts. We could improve the classification accuracy and sometimes regularize the natural language models to reduce the overfits. Our contribution to the data augmentation regarding Korean texts compose of three parts. 1) data augmentation with Spelling Correction, 2) Easy data augmentation based on part-of-speech tagging, and 3) Data augmentation with conditional Masked Language Modeling. Our experiments show that classification accuracy can be improved with the aids of our proposed methods. Due to the limit of computing facilities, we consider rather small-scale Korean texts only.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.494-497
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• 2012

Black marker cause unnatural problems between the existing various contents and marker. To solve this problem, we tested the various colors and color placement according to frequency of 3D objects. Based on this, infant's learning content system based NyARToolkit for the mobile-based augmented reality was implemented. We are solved the unnatural problems by insert to color marker in the Implemented system. and infant can study seamlessly because concentration increases by the familiar character on the markers.

• Annual Conference of KIPS
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• 2022.05a
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• pp.568-571
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• 2022

본 논문에서는 서술형 수학 문제의 자동 풀이 기술 개발을 위한 데이터 증강 기법인 MOO 를 제안한다. 서술형 수학 문제는 일상에서의 상황을 수학적으로 기술한 자연어 문제로, 인공지능 모델로 이 문제를 풀이하는 기술은 활용 가능성이 높아 국내외에서 다양하게 연구되고 있으나 데이터의 부족으로 인해 성능 향상에서의 한계가 늘 존재해 왔다. 본 논문은 이를 해결하기 위해 시중의 수학 문제들을 수집하여 템플릿을 구축하고, 템플릿에 적합한 풀이계획을 생성할 수 있는 중간 언어인 MOOLang 을 통해 생성된 문제에 대응하는 Python 코드 형태의 풀이와 정답을 생성할 수 있는 데이터 증강 방법을 고안하였다. 이 기법을 통해 생성된 데이터로 기존의 최고 성능 모델인 KoEPT를 통해 학습을 시도해본 결과, 생성된 데이터셋을 통해 모델이 원활하게 데이터셋의 분포를 학습할 수 있다는 것을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.209-212
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• 2013

The Nuri process of emphasis by the Ministry of Education to promote is standardized curriculum at the national level for the education and care. It is to improve the quality of pre-school education and Ensure a fair starting line early in life and It emphasizes character education in all areas of the window. Nuri the process of development of a the insect robot for the Creativity education Increased the interesting and educational effects. Assembly and the effect on learning of educational content using a VR educational robot using the existing floor assembly using the online website to help assemble and learning raised. Order to take advantage of information technology in the information-based society requires the active interest and motivation in learning, creative learning toddlers learning robot are also needed. A three-dimensional model of the robot, and augmented by linking through the marker, the target marker and the camera relative to the coordinate system of augmented reality, seeking to convert the marker to be used in augmented reality marker patterns within a pre-defined patternto be able to make a decision on what of. The fusion of a smart education through training and reinforcement the educational assembly of the robot in the real world window that is represented by a virtual environment in this paper to present a new form of state-of-the-art smart training, you will want to lay the foundation of the nation through the early national talent nurturing talent.

• Journal of IKEEE
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• v.26 no.3
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• pp.468-474
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• 2022

In this paper, we propose a method to implement a real-time fire alarm system using deep learning. The deep learning image dataset for fire alarms acquired 1,500 sheets through the Internet. If various images acquired in a daily environment are learned as they are, there is a disadvantage that the learning accuracy is not high. In this paper, we propose a fire image data expansion method to improve learning accuracy. The data augmentation method learned a total of 2,100 sheets by adding 600 pieces of learning data using brightness control, blurring, and flame photo synthesis. The expanded data using the flame image synthesis method had a great influence on the accuracy improvement. A real-time fire detection system is a system that detects fires by applying deep learning to image data and transmits notifications to users. An app was developed to detect fires by analyzing images in real time using a model custom-learned from the YOLO V4 TINY model suitable for the Edge AI system and to inform users of the results. Approximately 10% accuracy improvement can be obtained compared to conventional methods when using the proposed data.